Find your next role

Toronto · Full time

Line of Service Advisory Industry/Sector Not Applicable Specialism Technology Strategy Management Level Senior Associate Job Description & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions. Meaningful work you'll be part of As a Senior Associate, Azure Data Engineer, you will play a key role in designing and building data solutions on Azure. You will work closely with project teams to deliver high-quality data pipelines, ensure data integrity, and support deployment activities. Responsibilities include but are not limited to: Act as an expert in Azure Data Platform, including Azure Data Factory (ADF), Azure Databricks, Synapse Analytics, Event Hub, Blob Storage. Design and build scalable data pipelines for ingestion, transformation, and curation/normalisation of data. Implement data quality checks, error handling, and monitoring frameworks to ensure reliability. Apply strong knowledge of data modelling and data warehouse concepts to optimise architecture. Troubleshoot issues during development and testing phases, ensuring smooth deployment of data pipelines. Collaborate with data scientists, analysts, and business stakeholders to deliver robust solutions. Support pre-sales activities and RFP responses with technical input when required. Contribute to knowledge sharing and best practices within the team. Experiences and skills you’ll use to solve Bachelor’s degree in Computer Science, Engineering, or related field Hands-on experience with Azure data services: Data Factory, Synapse, Databricks, Event Hub, Blob Storage. Proficiency in SQL and Python; strong understanding of ETL/ELT processes. Hands-on experience with Power BI Knowledge of data quality frameworks and error handling techniques. Strong analytical and problem-solving skills; effective communicator. Preferred certifications: Microsoft Certified: Azure Data Engineer Associate (DP-203); Microsoft Certified: Fabric Analytics Engineer Associate; Databricks Certified Data Engineer Associate This role does not require professional engineering licensure and is not classified as a formal engineering position under provincial regulatory definitions. While individuals with a P.Eng designation are welcome to apply, the responsibilities of this role do not involve the practice of professional engineering as defined by applicable legislation PwC Canada is committed to cultivating an inclusive, hybrid work environment. Exact expectations for your team can be discussed with your interviewer This newly created role reflects our commitment to growth and delivering distinctive value for our clients and stakeholders . The salary range for this position is $84,700 - $134,700 . The posted salary range represents the expected hiring range for PwC locations in major city centres . Given our national recruiting approach, ranges may vary for positions in other locations. At PwC Canada, base salary is determined by your skills, experience, qualifications and work location. In addition to base salary, eligible employees may have opportunities to participate in variable incentive pay programs which are designed to reward individual and firm-wide achievements. We are committed to offering competitive compensation and adhere to all relevant pay transparency legislation. During the hiring process, our Talent Acquisition team will provide details about our comprehensive total rewards package. Why you’ll love PwC We’re inspiring and empowering our people to change the world. Powered by the latest technology, you’ll be a part of diverse teams helping public and private clients build trust and deliver sustained outcomes. This meaningful work, and our continuous development environment, will take your career to the next level. We reward your impact, and support your wellbeing, through a competitive compensation package, inclusive benefits and flexibility programs that will help you thrive in work and life. Learn more about our Application Process and Total Rewards Package at: https://jobs-ca.pwc.com/ca/en/life-at-pwc PwC Canada acknowledges that we work and live across Turtle Island, on the land that is now known as Canada, which are the lands of the ancestral, treaty and unceded territories of the First Nations, Métis and Inuit Peoples. We recognize the systemic racism, colonialism and oppression that Indigenous Peoples have experienced and still go through, and we commit to allyship and solidarity. Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture Development, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 28 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date We’re committed to providing accommodation throughout the application, interview, and employment process. If you require accommodation to be at your best, please let us know during the application process. The use of artificial intelligence (AI) in recruiting is just getting started, so we know you have questions about how and why we use it. At certain points during our recruiting process, we rely on AI to improve your experience. This could be during resume review or curating personalized job recommendations, asking you clarifying questions via a chatbot or during our interview scheduling to improve your experience. Our use of AI helps ensure we combat bias by evaluating candidates equally and fairly, without seeing identity information, such as your name, or gender for example). AI also helps us better predict successful hires by reviewing all applicants for a role and the relationship between your skills, experience and likely success at PwC Canada. While AI supports parts of our recruitment process, final hiring decisions always involve human review. For more information about our use and protection of your data, please refer to our Privacy Policy (https://www.pwc.com/ca/en/privacy-policy.html). Nous tenons à répondre à vos besoins tout au long du processus de demande d’emploi, d’entrevue et d’embauche. Si vous avez besoin de mesures d’adaptation pour être parfaitement à l’aise, faites-le-nous savoir à l’étape de la demande d’emploi. L’utilisation de l’intelligence artificielle (IA) dans le domaine du recrutement en est à ses balbutiements. Nous savons que vous pourriez vous demander comment et pourquoi nous y avons recours. À certains stades de notre processus de recrutement, nous comptons sur l’IA pour améliorer votre expérience. Par exemple, pendant l’examen du curriculum vitæ ou l’élaboration d’une liste de recommandations personnalisées, un agent conversationnel pourrait vous demander des précisions ou fixer avec vous un rendez-vous pour l’entrevue. L’IA nous aide à mieux lutter contre les préjugés, car l’évaluation des candidats se fait de façon juste et équitable, sans que les informations d’identification comme le nom ou le sexe soient connues. Elle nous permet également de mieux repérer les bons candidats pour un poste et d’évaluer le lien entre leurs compétences, leur expérience et leurs chances de réussir chez PwC Canada. Bien que l’IA facilite certaines étapes de notre processus de recrutement, les décisions finales d’embauche sont toujours prises par des personnes. Pour en savoir plus sur l’utilisation et la protection de vos données personnelles, consultez notre politique sur la protection des renseignements confidentiels (https://www.pwc.com/ca/fr/privacy-policy.html).

Remote - Canada

Who we are Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale. Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term. About the role: Samsara is looking for a Software Engineer to join our Data Platform team , which owns and develops the core analytical platform across Samsara. This team builds and maintains the infrastructure that powers Samsara’s data lake, distributed compute platform, and the systems that move data from our production data stores into our lakehouse. As a Software Engineer on Data Platform, you will design, build, and operate reliable, scalable, and secure infrastructure for ingesting, processing, cataloging, and accessing petabytes of data. You will work on the foundational systems that enable engineers, data scientists, analysts, and product teams across Samsara to build customer-facing features, train models, develop operational insights, and support the company’s long-term AI and analytics roadmap. This is a specialized software engineering role focused on data infrastructure. You will work on systems such as Spark and Databricks infrastructure, Delta Lake on S3, data replication from primary data stores such as RDS and DynamoDB, orchestration and metadata services, internal data libraries, and infrastructure tooling across the big data ecosystem. This role is not an analytics or business data engineering role. If your experience is primarily focused on SQL modeling, BI dashboards, ETL tools, or building business-facing data marts, this role is likely not the right fit. The ideal candidate is a software engineer with deep experience building and operating production data platforms, distributed systems, or large-scale ingestion infrastructure. This is a remote position open to candidates residing in Canada. Relocation assistance will not be provided for this role. You should apply if: You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact – helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely. You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go. You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes. You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we’re all racing toward our connected operations vision, and we intend to win – together. In this role, you will: Design, build, and operate high-scale data ingestion and replication systems from Samsara’s primary production data stores, including RDS, DynamoDB, internal APIs, and event-driven systems, into our data lakehouse. Build and maintain reliable, scalable, and modern data platform infrastructure capable of handling petabytes of data across Samsara’s analytics, AI, product, and operational use cases. Improve the reliability, observability, scalability, security, and developer experience of Samsara’s Spark and Databricks-based data processing platform. Develop internal libraries, APIs, frameworks, and tooling in languages such as Go and Python to help teams across Samsara move, process, discover, and access data safely and efficiently. Work on foundational data lake and lakehouse technologies, including Delta Lake on S3, data catalogs, metadata services, orchestration systems, and platform automation. Collaborate closely with infrastructure, product engineering, data science, analytics, security, and data engineering teams to understand platform needs and deliver durable, scalable solutions. Stay connected to modern data platform technologies and help shape Samsara’s long-term data infrastructure roadmap, including support for AI, privacy, security, global scale, and customer-facing data products. Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices Minimum requirements for the role: 4+ years of professional software engineering experience in production environments. 4+ years of experience building or maintaining large-scale production data infrastructure, data platforms, distributed systems, or data lake systems. Strong experience with Apache Spark or similar distributed data processing systems. Experience operating production infrastructure in AWS, including services such as S3, RDS, DynamoDB, SQS, Kinesis, Lambda, or similar. Experience designing, building, and operating reliable systems with strong ownership of scalability, observability, security, and operational excellence. Proficiency in at least one production programming language such as Go, Python, Scala, or Java. Ability to collaborate effectively with cross-functional partners, including software engineers, data scientists, analysts, security teams, and product stakeholders. An ideal candidate also has: Experience with Databricks, Delta Lake, or similar lakehouse technologies such as Iceberg or Hudi. Experience building data replication or ingestion systems from OLTP data stores into a data lake or lakehouse. Experience with Infrastructure-as-Code tools such as Terraform or CloudFormation. Familiarity with data catalogs, metadata systems, and data discovery tools such as Unity Catalog, Hive Metastore, DataHub, or Amundsen. Experience with orchestration systems such as Airflow, Dagster, or Prefect. Experience with streaming data, event-driven architectures, or systems that handle late-arriving or mutable data. Familiarity with containerization or orchestration technologies such as Docker, Kubernetes, ECS, or Fargate. Experience building internal platforms, libraries, or developer tooling used by other engineering teams. Experience contributing to data infrastructure roadmaps, evaluating new technologies, and driving improvements that create leverage for internal and external customers. The compensation range shown spans approved pay zones for this role. Your primary work location determines the range applicable to you, which may be narrower than the full range displayed. The range of annual base salary for full-time employees for this position is below. Please note that base pay offered may vary depending on factors including your city of residence, job-related knowledge, skills, and experience. This role is also eligible for an initial RSU grant with no vesting cliff, and ongoing refresh opportunities tied to performance, subject to plan terms and conditions. Learn more about our total rewards and benefits below. Annual Base Salary $106,675 — $138,050 CAD Total Rewards At Samsara, we build for the people who keep the global economy moving. We want owners, not passengers, which is why our rewards are designed to fuel high-impact builders. Our compensation program delivers above-market total compensation through a combination of base salary, performance-based bonus/variable pay, and equity (for eligible roles) in a high-growth public company. We meaningfully differentiate pay for our top performers, who have the opportunity to earn above-market compensation that can outpace the broader market over time. Beyond compensation, we provide the foundations that enable long-term success: a flexible, employee-led remote model, a professional development stipend, comprehensive health and parental leave plans, and more. If you’re ready to build for the long term and own the outcome, your journey starts here. Flexible Working At Samsara, we embrace a flexible working model that caters to the diverse needs of our teams. Our offices are open for those who prefer to work in-person and we also support remote work where it aligns with our operational requirements. For certain positions, being close to one of our offices or within a specific geographic area is important to facilitate collaboration, access to resources, or alignment with our service regions. In these cases, the job description will clearly indicate any working location requirements. Our goal is to ensure that all members of our team can contribute effectively, whether they are working on-site, in a hybrid model, or fully remotely. All offers of employment are contingent upon an individual’s ability to secure and maintain the legal right to work at the company and in the specified work location, if applicable. Belonging at Samsara At Samsara, we welcome everyone regardless of their background. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, protected veteran status, disability, age, and other characteristics protected by law. We depend on the unique approaches of our team members to help us solve complex problems and want to ensure that Samsara is a place where people from all backgrounds can make an impact. Accommodations Samsara is an inclusive work environment, and we are committed to ensuring equal opportunity in employment for qualified persons with disabilities. Please email accessibleinterviewing@samsara.com or click here if you require any reasonable accommodations throughout the recruiting process. Our Commitment to Authenticity We use Tofu , a fraud detection tool, to validate the authenticity of applications and protect against identity fraud. This ensures we are connecting with real people and allows us to prioritize genuine candidates. Please see Samsara’s Candidate Privacy Notice for more information. Fraudulent Employment Offers Samsara is aware of scams involving fake job interviews and offers. Please know we do not charge fees to applicants at any stage of the hiring process. Official communication about your application will only come from emails ending in @samsara.com, @us-greenhouse-mail.io or @mail3.guide.co. For more information regarding fraudulent employment offers, please visit our blog post here .

Remote - CA

Who we are Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale. Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term. About the role: Want to build the data foundation powering AI and self-serve analytics at scale? As part of Samsara's Marketing Data and Analytics (MDA) Engineering team, you will shape the technical roadmap alongside our BI and Data Science peers. You will architect core Databricks pipelines, Gold Layer tables, and semantic models, turning ambitious, ambiguous business challenges into high-value data products, autonomous agents, and cross-functional automation. This role is open to candidates residing in the US. You should apply if: You want to impact the industries that run our world: Your efforts will result in real-world impact – helping to keep the lights on, get food into grocery stores, reduce emissions, and most importantly, ensure workers return home safely. You are the architect of your own career: If you put in the work, this role won’t be your last at Samsara. We set up our employees for success and have built a culture that encourages rapid career development, countless opportunities to experiment and master your craft in a hyper growth environment. You’re energized by our opportunity: The vision we have to digitize large sectors of the global economy requires your full focus and best efforts to bring forth creative, ambitious ideas for our customers. You want to be with the best: At Samsara, we win together, celebrate together and support each other. You will be surrounded by a high-calibre team that will encourage you to do your best. In this role, you will: Partner on defining the strategy and multi-quarter roadmap for MDA's data and AI foundation. Architect and own Samsara's marketing data infrastructure: ETL/ELT pipelines, Databricks Gold Layer tables, and the core data models that power segmentation, targeting, automation, and analytics. Design the semantic layers, data dictionaries, and structured documentation that enable self-serve BI and conversational analytics, partnering with the BI team to ensure core sales and marketing KPIs are built on trusted, well-modeled data. Translate ambiguous business questions from Marketing, Sales, and R&D into clear requirements and scalable solutions, working autonomously without dedicated PM support and influencing decisions with data and sound reasoning. Lead complex, cross-team initiatives end to end: stand up new data pipelines and integrations quickly, manage risk across interdependent teams, and own the reliability and data quality of what ships. Serve as the senior technical lead for the team's hardest problems: raise the bar for engineering quality and code review, remove bottlenecks that slow multiple teams, and mentor engineers and analysts. Drive the strategic use of AI to solve ambiguous, high-impact problems: build AI-enabled data products and agents, with the integrations, retrieval pipelines, and evaluation practices that keep them reliable and trustworthy. Identify and automate manual workflows with AI across Marketing and GTM teams, taking ideas from concept to prototype to production and influencing org roadmaps. Ship high-quality Python and SQL, increasingly by directing agentic coding tools, while holding a high bar for reviewing and verifying AI-generated work before it reaches production. Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices. Minimum requirements for the role: 8+ years of experience in data engineering, analytics engineering, or AI engineering, including deep hands-on data engineering experience. Expert-level Python and SQL, with strong hands-on data modeling and DBT experience. Deep experience with data warehouse and lakehouse architectures, ETL/ELT, and the modern data stack, including hands-on Databricks (or similar, such as Snowflake or BigQuery). Experience building semantic layers and structured documentation optimized for AI ingestion and agentic workflows. Agentic coding tools (e.g., Claude Code, Cursor) are part of your regular workflow, and you verify and take ownership of AI-generated output. Experience building, shipping, evaluating, and monitoring LLM or agent systems in production. Track record of leading complex, cross-team data initiatives, including independent requirements gathering with technical and non-technical stakeholders. Experience supporting Marketing, Sales, or Product teams. An ideal candidate also has: Experience working with Databricks and building AI Agents within the ecosystem. Software engineering background beyond data or AI engineering, with a track record of turning ambiguous, unfamiliar problems into well-architected, delivered solutions. Expertise in data visualization and building dashboards for sales and marketing KPIs. Familiarity with go-to-market data and systems: CRM (e.g., Salesforce), marketing automation, web analytics, and MarTech tools. Experience building interactive applications with Streamlit, Claude workflows, or web frameworks. Data science, machine learning, or predictive analytics experience. Comfort working in an exploratory environment, testing and iterating on new data sources and methodologies. The compensation range shown spans approved pay zones for this role. Your primary work location determines the range applicable to you, which may be narrower than the full range displayed. The range of annual base salary for full-time employees for this position is below. Please note that base pay offered may vary depending on factors including your city of residence, job-related knowledge, skills, and experience. This role is also eligible for an initial RSU grant with no vesting cliff, and ongoing refresh opportunities tied to performance, subject to plan terms and conditions. Learn more about our total rewards and benefits below. Annual Base Salary $137,445 — $231,000 USD Total Rewards At Samsara, we build for the people who keep the global economy moving. We want owners, not passengers, which is why our rewards are designed to fuel high-impact builders. Our compensation program delivers above-market total compensation through a combination of base salary, performance-based bonus/variable pay, and equity (for eligible roles) in a high-growth public company. We meaningfully differentiate pay for our top performers, who have the opportunity to earn above-market compensation that can outpace the broader market over time. Beyond compensation, we provide the foundations that enable long-term success: a flexible, employee-led remote model, a professional development stipend, comprehensive health and parental leave plans, and more. If you’re ready to build for the long term and own the outcome, your journey starts here. Flexible Working At Samsara, we embrace a flexible working model that caters to the diverse needs of our teams. Our offices are open for those who prefer to work in-person and we also support remote work where it aligns with our operational requirements. For certain positions, being close to one of our offices or within a specific geographic area is important to facilitate collaboration, access to resources, or alignment with our service regions. In these cases, the job description will clearly indicate any working location requirements. Our goal is to ensure that all members of our team can contribute effectively, whether they are working on-site, in a hybrid model, or fully remotely. All offers of employment are contingent upon an individual’s ability to secure and maintain the legal right to work at the company and in the specified work location, if applicable. Belonging at Samsara At Samsara, we welcome everyone regardless of their background. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, protected veteran status, disability, age, and other characteristics protected by law. We depend on the unique approaches of our team members to help us solve complex problems and want to ensure that Samsara is a place where people from all backgrounds can make an impact. Accommodations Samsara is an inclusive work environment, and we are committed to ensuring equal opportunity in employment for qualified persons with disabilities. Please email accessibleinterviewing@samsara.com or click here if you require any reasonable accommodations throughout the recruiting process. Our Commitment to Authenticity We use Tofu , a fraud detection tool, to validate the authenticity of applications and protect against identity fraud. This ensures we are connecting with real people and allows us to prioritize genuine candidates. Please see Samsara’s Candidate Privacy Notice for more information. Fraudulent Employment Offers Samsara is aware of scams involving fake job interviews and offers. Please know we do not charge fees to applicants at any stage of the hiring process. Official communication about your application will only come from emails ending in @samsara.com, @us-greenhouse-mail.io or @mail3.guide.co. For more information regarding fraudulent employment offers, please visit our blog post here .

USA, CA, Pleasanton · Full Time

Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too. About the Team We are hiring Sr ML Engineers across two teams. Admin Central is building the future of how administrators work across Workday—turning a fragmented patchwork of tools and disconnected AI into a single, unified experience. Within Admin Central, Workday implementations move from being driven by human effort to being powered by intelligence designed into the platform. The Business Process Optimize (BPO) team powers the underlying platform infrastructure. You’ll build mission-critical distributed systems, high-availability usage pipelines, new agentic functionality, and event-driven data flows across global product regions to ensure enterprise billing integrity at scale. If you're excited to build from scratch, move fast, and transform how thousands of admins work every day, come join us! About the Role Key Responsibilities ML Infrastructure & Pipeline Engineering: Architect, deploy, and maintain end-to-end Machine Learning pipelines—from distributed data ingestion and feature engineering to model training, evaluation, and production deployment. Agentic AI & Recommendation Engines: Design algorithms and LLM-driven recommendation features (e.g., IDD insights, next-best-action models) that optimize agentic workflows and tool usage. Low-Latency Inference & Scaling: Optimize real-time model inference and scoring microservices to ensure sub-second response times across high-concurrency multi-tenant environments. LLM & Agentic Observability: Integrate telemetry and tracing (OpenTelemetry, LangChain, LangSmith) into ML pipelines to track model performance, prompt/response drift, and execution efficiency. Data & Feature Store Architecture: Collaborate with core backend engineers to leverage big data platforms (ClickHouse, Apache Iceberg, Spark) for high-dimensional feature retrieval and analytics. Cross-Functional Leadership: Partner closely with Product Managers, Data Engineering, SRE, and Legal/Compliance to translate complex business and governance requirements into scalable ML solutions. About You Basic Qualifications 8+ years of experience in machine learning development, researching, developing, and implementing advanced machine learning models and techniques, with at least 4+ years focused explicitly on building, deploying, and operating production Machine Learning systems at scale. 5+ years of experience and proficiency in deep learning, natural language processing (NLP), and GenAI/LLM orchestration, utilizing frameworks and libraries such as PyTorch, TensorFlow, Scikit-learn, LangChain, and LlamaIndex, alongside proficiency in Java, Go, Scala, or C++ for high-performance backend systems. Other Qualifications Data Processing & Pipelines: Strong ability in distributed processing (Spark, Flink, Kafka) and high-throughput columnar/vector storage (ClickHouse, Pinecone, Milvus) to design robust ML data pipelines. AI/ML Expertise: Solid knowledge of RAG architectures, LLM fine-tuning, intent classification, and recommendation engines—applying ML algorithms and Model-Based Design (including MCP tooling and structured agentic execution paths) to multi-agent orchestration, contextual reasoning, and workflow optimization. Data Analysis & Feature Engineering: Experience leading EDA on multi-tenant execution logs to validate prompt/response accuracy and optimize tool usage, paired with strong feature engineering skills for vector embeddings, feature stores, and multi-tenant data isolation. Model Lifecycle: Experience leading model building (foundation model adaptation, prompt engineering, fine-tuning, low-latency inference) and deep understanding of the model development lifecycle, including MLOps platforms (Kubeflow, MLflow, Airflow, SageMaker) for monitoring, latency tracking, and retraining at scale. Technical Stack: Strong proficiency in Python and ML libraries (PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn, LangChain, LangSmith, DSPy), with experience deploying scalable ML systems in cloud-native production using Docker, Kubernetes, gRPC/REST APIs, and CI/CD under strict high-availability (99.9% uptime) and low-latency SLAs. Team Collaboration: Strong ability to mentor team members, drive cross-functional technical alignment, draft system design specs/model cards, and communicate technical and governance decisions. Education: Bachelor's in Computer Science, Data Science, Machine Learning, Applied Mathematics, Statistics, or Engineering; Master's or PhD strongly preferred. Workday Pay Transparency Statement The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please click here . Primary Location: USA.CA.Pleasanton Primary Location Base Pay Range: $192,000 USD - $288,000 USD Additional US Location(s) Base Pay Range: $163,000 USD - $288,000 USD Our Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter. Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans. Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law. Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law. If you require a reasonable accommodation, you may email accommodations@workday.com , as far in advance as possible. Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process! At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not. In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

USA, CA, Pleasanton · Full Time

Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too. About the Team We are hiring engineers on two different teams. Admin Central is building the future of how administrators work across Workday—turning a fragmented patchwork of tools and disconnected AI into a single, unified experience. Within Admin Central, Workday implementations move from being driven by human effort to being powered by intelligence designed into the platform. The Business Process Optimize team powers the underlying platform infrastructure. You’ll build mission-critical distributed systems, high-availability usage pipelines, new agentic functionality, and event-driven data flows across global product regions to ensure enterprise billing integrity at scale. If you're excited to build from scratch, move fast, and transform how thousands of admins work every day, come join us! About the Role About the Role As a Principal Software Engineer you will lead the architecture and implementation of Workday’s next-generation AI platforms and autonomous agent frameworks. You’ll sit at the intersection of machine learning, event-driven data systems, and enterprise platform engineering—transforming cutting-edge AI research into production-ready, highly reliable systems handling tens of millions of daily requests for hundreds of enterprise tenants (including over 100+ Tier-0 enterprise tenants). In this hands-on, high-impact role, you will design the ML infrastructure, multi-agent orchestration layers, and high-availability usage pipelines that power enterprise-grade decision-making, usage tracking, automatic tenant maintenance, and billing integrity across international regions. Your Primary Focus Agentic AI & Orchestration: Design, implement, and maintain advanced agentic capabilities, including tool calling, multi-agent workflows, long-range planning, reasoning frameworks, and human-in-the-loop integrations. Scalable ML Infrastructure: Build secure, high-throughput REST services and event-driven data pipelines using Python, AWS, Kubernetes, and cloud-native tech. Architect multi-tenant runtimes that deliver fast, low-latency inference to millions of global users. MLOps & Enterprise Reliability: Establish end-to-end MLOps standards—including CI/CD automation, observability, evaluation frameworks, model monitoring, and privacy/anonymization guardrails—ensuring systems are explainable, secure, and production-resilient. Technical & Strategic Leadership: Partner closely with software engineers, Product Managers, Data Engineering, SRE, and Legal/Compliance stakeholders to turn ambiguous business needs into scalable technical designs and long-term data-governance strategies. About You Basic Qualifications 12+ years in ML development and R&D leadership, including 8+ years with advanced ML methodologies, distributed frameworks, and cloud-based platforms — designing complex, scalable, production-grade ML systems. 6+ years building and hosting scalable ML services, microservices, and high-throughput data pipelines in production using Java, Go, Scala, or Python. 4+ years working with LLMs, generative AI, RAG pipelines, and autonomous agent frameworks for real-world enterprise applications. Other Qualifications Data Processing & Pipelines: Expert in high-throughput streaming (Kafka), real-time feature extraction (Spark/Flink), and distributed columnar storage (ClickHouse, Iceberg) to architect large-scale ML pipelines. AI/ML Expertise: Deep knowledge of deep learning, LLM orchestration, RAG, and agentic systems — applying ML algorithms and Model-Based Design (including MCP integrations and tool-use frameworks) to multi-agent coordination, intent classification, and workflow optimization. Data Analysis & Feature Engineering: Proven ability to lead EDA on multi-tenant agentic workflows to shape data strategy, paired with mastery of high-dimensional embeddings, vector database management, and data isolation. Model Lifecycle: Proven ability to lead model building, fine-tuning, and deployment of domain-specific foundation models — including Kubernetes/Docker deployment, automated CI/CD retraining, and managing drift/latency at scale. Technical Stack: Mastery of Python and the ML ecosystem (PyTorch, TensorFlow, LangChain, LangSmith, LlamaIndex, NumPy, Pandas, Scikit-learn), with strong experience deploying production systems on PostgreSQL, Redis, Kafka, and cloud infrastructure (AWS/GCP/Azure). Team Leadership: Exceptional collaboration and mentoring skills — technically leading cross-functional pods, driving sprint planning, and translating technical/governance decisions for executives. Education: Bachelor's in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field (or equivalent experience); Master's or PhD strongly preferred. Workday Pay Transparency Statement The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please click here . Primary Location: USA.CA.Pleasanton Primary Location Base Pay Range: $228,000 USD - $342,000 USD Additional US Location(s) Base Pay Range: $190,600 USD - $342,000 USD Our Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter. Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans. Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law. Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law. If you require a reasonable accommodation, you may email accommodations@workday.com , as far in advance as possible. Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process! At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not. In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

Canada, BC, Vancouver | USA, GA, Atlanta · Full Time

Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too. About the Team Workday stands at a pivotal point in its evolution and growth. As we accelerate our Enterprise AI Transformation we must focus with equal intensity on scaling our execution to enable a rapid speed of continuous innovation for our customers. The Product & Technology (P&T) Operations Analytics & Tools Team develops decision-ready internal products that turn complex organizational data into targeted leadership action. Our vision is to: Power the strategic intelligence that scales how P&T operates with alignment and speed. About the Role We're looking for a business, product, and customer-oriented Senior Product Data Scientist to be the analytics partner for the Workday Data Cloud business. This role requires focused passion and excitement unlocking data insights that directly tie to strategic execution. This role sits at the intersection of Workday's Data Cloud business, partnering directly with the Data Cloud organization (SVP/GM, Product Management, Engineering, and GTM teams) to bring analytical rigor and powerful business insights to a fast-growing, consumption-based product line. You will be the investigatory lead on a number of broad business questions. You will dive into the raw business data, find the root cause, and deliver an opinionated, decision-ready conclusion, not just more data. You'll need to become a genuine subject-matter expert in Workday Data Cloud's business data landscape, working closely with the Workday Data Cloud GM and Product Management team. Your findings, and the curated data and documentation you produce along the way, should compound: feeding a shared knowledge base that makes the next question easier to answer, for you and for AI-assisted tooling built on top of the same body of work. Key Responsibilities Serve as the business analytics domain expert for Workday Data Cloud, providing technical and strategic thought leadership. Partner cross-functionally across Go-To-Market (GTM) and Product teams to develop end-to-end views of the business, connecting the dots between top-of-funnel demand growth, sales pipeline, and downstream product usage. Translate complex data models into compelling narratives and stories (including interactive visualizations and executive presentations) that drive organizational clarity. Operate directly with SVP/GM-level stakeholders, translating a stream of layered, high-velocity questions into structured analysis without needing fully scoped requirements up front. Translate ambiguous business, data, and platform questions into simple and focused conclusions, independently and with strategic judgment Support consumption-based pricing and impact analysis for Workday Data Cloud, including sensitivity analysis, exploring new business models and driving business growth Navigate real data-maturity and instrumentation gaps with autonomy: identifying what already exists, what must be built, and when to escalate. Contribute well-documented, curated data assets and context back into the shared knowledge base so that analysis compounds over time and can eventually be self-served. Design and influence Workday Data Cloud internal business data connections, collaborating with Product Management and engineering teams on the design, scalability, and sustainability of associated pipelines. Leverage strong data ETL and data processing expertise to manage multi-step flows across product telemetry and observability systems Demonstrate urgency and autonomy in problem-solving, proactively navigating cross-functional teams to identify and implement solutions for both known and emerging business challenges. About You You possess a deep interest in grasping the complex challenges that businesses face, and you are excited by solving problems. You have strong business acumen and are outcomes focused. Learning new tools and technologies motivates you. You embody the qualities of an insightful, thoughtful, and reliable teammate - and you expect the same of your teammates. You thrive in a fast-paced, tech start-up like environment where the best ideas win. “Think Like a Scientist” is ingrained in how you work - always hypothesizing, always experimenting, always learning. You're energized, not intimidated, by building trust, process, and domain expertise in a new, growing business space. You default to curating and documenting what you learn, because you know the same data landscape will get harder questions tomorrow. You're comfortable moving between hands-on data work and strategic, executive-level framing. Basic Qualifications 8+ years of experience with advanced analytics, statistical modeling, and/or data science 8+ years experience simplifying complex technical concepts for diverse stakeholders. 6-8 years experience working autonomously in a highly matrixed, collaborative corporate environment. 5+ years experience in business/product analytics, applied data science, or a related quantitative role, ideally supporting a product or platform organization. 5+ years experience in enterprise BI platforms (e.g.,Tableau, Sigma ) Other Qualifications: Strong SQL and data-modeling skills; comfortable working directly in raw, partially documented, or partially instrumented datasets. Familiarity with front-end components or frameworks (e.g., React, Node.js, JavaScript) to help collaborate with engineering peers. Working familiarity with cloud data pipelines/ETL concepts (e.g., Airflow) sufficient to partner effectively with data engineering and platform product management teams. Experience with SaaS pricing analytics or usage-based/consumption pricing models specifically. Strong project management skills Experience applying organizational change management principles Experience working within an Agile/Scrum framework. Experience within the SaaS, cloud, or enterprise technology industries Strong communication and data storytelling skills Demonstrated experience designing, developing, and maintaining enterprise production-level data science-based products for business decision-making Experience on AWS stack (Redshift, Sagemaker), scripting languages (Python and R) Degree in a quantitative field (Computer Science, Engineering, Statistics, Operations Research, Economics, or a related field) or equivalent practical experience. Understanding of product management fundamentals Workday Pay Transparency Statement The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits in Canada, please click here . For more information regarding Workday’s comprehensive benefits in the US, please click here . Primary Location: CAN.BC.Vancouver Primary CAN Base Pay Range: $124,400 - $186,600 CAD Additional US Location(s) Base Pay Range: $148,200 USD - $263,300 USD Our Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter. Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans. Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law. Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law. If you require a reasonable accommodation, you may email accommodations@workday.com , as far in advance as possible. Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process! At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not. In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

San Francisco, CA | New York City, NY; Seattle, WA

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's go-to-market teams are scaling quickly, and the decisions they make, from who to sell to and how to cover them to where to invest next, are only as good as the intelligence and infrastructure underneath them. As a Data Engineer on the GTM Systems data foundations team, you'll help build that layer: the data products that give sellers, operators, and analysts a rich, current, and trusted picture of the market, and the engineering rigor that lets our GTM systems run reliably as the business grows. This is an engineering role that goes beyond pipelines. You'll treat GTM data as a product and a platform: built once, kept current, and available wherever people work. Alongside the build, you'll help shape what the data means: how attributes are defined, which sources are trusted, and how the business puts them to use. The role sits at the intersection of the sales organization, the data organization, and the systems that data flows through. You'll partner closely with Sales Strategy and Operations, Finance, Data Science, and the central data engineering team. Key responsibilities Bring disparate internal and external sources together: orchestrate, model, and normalize first-party product and revenue data alongside third-party data into one usable understanding of the company landscape Build and maintain identity and entity resolution, so every source attaches to one trusted record for each company and the relationships between companies are clear Help build the canonical layer where key attributes are defined once and mean the same thing everywhere, with clear sourcing logic, provenance, and freshness Turn data into intelligence: scores, signals, and AI-generated attributes that help GTM teams prioritize and act, held to the same quality bar as any other source Deliver that intelligence to the surfaces where teams work, including the CRM, and bring production discipline to how data moves through those systems Operate what you build as a living system, with observability, data quality, cost, security, and access controls designed in, so problems surface before the field sees them Partner with the owners of GTM processes such as planning, segmentation, and routing to settle definitions, make clear commitments, and communicate tradeoffs Make the platform easy for other teams to build on, so work is contributed once and not rebuilt in silos Minimum qualifications Experience as a data engineer or analytics engineer building and operating production pipelines and data models Strong SQL and Python, and experience with modern transformation and orchestration tooling on a cloud data warehouse Experience making messy data from many sources usable, including record matching, deduplication, and reconciling conflicting values Familiarity with go-to-market data and the CRM systems it flows through Judgment beyond the pipeline: weighing data sources, shaping definitions with business partners, and making calls on data quality Clear written and verbal communication with technical and non-technical partners Regular hands-on use of AI tools in your engineering work Preferred qualifications 5+ years of experience in data engineering, analytics engineering, or GTM data roles Experience building a shared data product or platform that several teams depend on and contribute to Experience with company data such as firmographics, corporate hierarchies, or master data management Experience using LLMs inside data pipelines and evaluating their output Hands-on Salesforce experience, including working at large data volumes Experience supporting GTM planning processes such as territory design, segmentation, or scoring The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Palo Alto, CA

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. SOFTWARE ENGINEER, DATA ENGINEERING (X) As a Data Engineer in X product engineering team, you will play a key role in providing comprehensive data solutions that own or serve a wide range of stakeholders, including our end-users and internal teams such as Product engineering, Algorithm, Legal, Finance and Sales. Our work utilizes AI, distributed computing and hybrid storage technologies, but extends beyond purely data-centric solutions, encompassing non-data-related challenges, ultimately maximizing the potential of data for the benefit of our diverse user base. You'll help build and operate a distributed data platform that powers hundreds of realtime and batch pipelines processing billions of events per day. The team runs like an internal startup — we own problems end to end, from raw event streams to the datasets, tooling, and metrics that product, growth, safety, and business teams depend on daily. RESPONSIBILITIES: Design, build, and operate production-grade realtime and batch pipelines that ingest, process, validate, and deliver data powering user-behavior insights and product decisions Create shared datasets, fact tables, and internal data products that let other teams analyze, debug, and improve product performance Prototype and build tooling that automates and accelerates internal data workflows — backfills, dashboards, report generation, and self-serve access to data Own data correctness end to end: validate with output invariants, denominator reconciliation, and independent recomputation, and lead root-cause investigations when key metrics move unexpectedly Move fluidly across query engines and frameworks (e.g., BigQuery, Trino, Clickhouse for analytics; Flink, Kafka, Spark/Scalding for streaming and batch), choosing the right tool and adapting quickly to new infrastructure and environments Partner across product and business teams to surface where data gaps exist and prioritize the highest-impact opportunities for new data acquisition and improvement Iterate quickly on feedback, shipping the smallest useful increment with a strong bias toward efficient, accurate, and reliable solutions BASIC QUALIFICATIONS: 3+ years of professional software engineering experience Experience with Python, Rust, Scala, Go or Java, and data pipeline toolings and distributed systems PREFERRED SKILLS AND EXPERIENCE: Software engineering experience in data engineering or distributed systems Knowledge of realtime and batch data processing tools such as Spark/Kafka/Flink/SQL and various storage systems in RMDBs/NoSQL Experience solving large scale problems and comfortable doing incremental quality work while building brand new systems to enable future quality improvements Proven records of interpreting product requirements into engineering implementation plans, and effectively communicating with different groups (AI, product, marketing/sales and engineering) COMPENSATION AND BENEFITS: $125,000 - $400,000 USD Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice .

Palo Alto, CA

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. HUMAN DATA ENGINEER You will ensure engineering teams get the right data they need—high-quality tasks and evaluations—by crafting and executing high-value Human Data projects. You sit at the intersection of engineering and data operations: partnering with model teams, designing projects that capture meaningful signals, and driving data yield and eval lift. This is a hands-on technical role for engineers who deeply understand training and evaluation and want to influence data strategy. RESPONSIBILITIES: Partner with model and engineering teams to understand needs and translate them into high-value data projects and evaluation strategies Own end-to-end delivery of critical data and eval projects that capture meaningful training signals and support rapid model development Build tools and systems to measure data effectiveness (data yield, eval lift, usage), and run evaluations yourself to continuously improve quality Maintain rigorous data integrity and truthfulness, including validation processes for factual accuracy; prioritize quality over quantity Research, implement, and evaluate techniques for data collection, annotation, generation, and multi-modal integration Shape Grok’s behavior and domain performance through targeted data work Design and improve annotation workflows, labeling interfaces, and related tools with a focus on data quality and integrity Act as a liaison between engineering, technical staff, and tutoring / Human Data teams to drive alignment and knowledge sharing Collaborate with Human Data Ops and stakeholders to scale projects, share learnings, and contribute to demand forecasting; report status, insights, and blockers for rapid decisions BASIC QUALIFICATIONS: Bachelor’s degree in engineering, computer science, or a STEM discipline; OR 4+ years of experience in lieu of a degree Experience collaborating with cross-functional teams (engineering, research, product, or annotation/operations groups) Experience analyzing datasets to identify trends, anomalies, quality issues, or integrity problems PREFERRED SKILLS AND EXPERIENCE: Master’s degree or higher in a relevant technical field Direct experience curating, evaluating, or improving training or evaluation datasets for large language models or other AI/ML systems Experience designing, supporting, or optimizing annotation tools, labeling interfaces, or data workflows that prioritize factual accuracy and data integrity Familiarity with multimodal data (text + images, code, or other modalities) or domain-specific data (science, mathematics, programming, recent events, etc.) Experience conducting model or dataset evaluations focused on quality, truthfulness, or alignment with product goals Experience in a scripting language like Python Experience in SQL or other data analysis tools ADDITIONAL REQUIREMENTS: Weekend work may be required Travel to other SpaceXSI sites may be required COMPENSATION AND BENEFITS: $144,000 - $220,000 USD Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice .

Palo Alto, CA

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. SR. ANALYTICS ENGINEER (X) We are seeking a skilled Senior Analytics Engineer to build and maintain robust data systems that enable high-impact quantitative analysis and business decision-making. This role combines strong software engineering practices with expertise in large-scale data processing and advanced analytical methods to deliver reliable, scalable solutions across the organization. This is an opportunity to work on mission-critical systems that power quantitative decision-making at global scale. RESPONSIBILITIES: Design, implement, and optimize end-to-end data pipelines for processing high-volume datasets using tools such as Spark, Kafka, and/or Flink Develop quantitative models and statistical frameworks to support experimentation, forecasting, and performance measurement Build and maintain data infrastructure that ensures data quality, consistency, and accessibility for analytical workflows Collaborate with product engineering, product, and operations teams to translate business requirements into production-grade data systems and insights Conduct A/B tests, causal analysis, and performance evaluations to drive measurable improvements in key metrics Implement monitoring, alerting, and automation for data systems to support real-time decision support Mentor team members on best practices for scalable data engineering and quantitative problem-solving BASIC QUALIFICATIONS: Bachelor's or master's degree in computer science, statistics, applied mathematics, or quantitative field 5+ years of experience building production data pipelines and infrastructure at scale Experience in Python, SQL, and distributed computing frameworks (e.g., Spark, Flink, Hadoop) PREFERRED SKILLS AND EXPERIENCE: Demonstrated expertise in statistical methods, predictive modeling, hypothesis testing, and experimental design Solid understanding of cloud services for data storage, processing, and orchestration Excellent problem-solving skills with a focus on delivering business impact through reliable systems Prior work in consumer technology, or social media domains Experience with real-time streaming systems and low-latency data processing Contributions to open-source data tools or publications on large-scale analytics systems Track record of reducing operational costs or improving system efficiency through data optimizations Have the ability to bridge engineering excellence with rigorous analytical approaches COMPENSATION AND BENEFITS: $180,000 - $440,000 USD Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice .

Vancouver, BC

Analytical Engineering Manager at Asana in Vancouver, BC focuses on You sit at the intersection of Data Engineering, Analytics, and Data Science, and you are accountable for whether. This role is based in our Vancouver office with an office-centric hybrid schedule.

Reddit

Chicago, IL; Los Angeles, CA; New York City, NY; San Francisco, CA

Senior GTM Insights Automation Manager at Reddit in Chicago, IL; Los Angeles, CA; New York City, NY; San Francisco, CA focuses on Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet.

Toronto, Ontario, Canada · Full time

This role bridges business and technical teams to support an enterprise Data & AI strategy. The Data Business Analyst will translate business needs into data requirements, contribute to data modeling and glossary management, and drive data integration initiatives. The position requires 2-5 years of experience in data governance or a similar enterprise data role, with strong SQL skills and knowledge of data quality and cloud platforms.

Toronto, Canada

Software Developer, Data Engineering at Robinhood in Toronto, Canada focuses on An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history.

Toronto, Canada

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. We are looking for an experienced backend software engineer to join our Road Safety & Telematics team. At Lyft, Telematics data is used to make Lyft safer by reducing the frequency and severity of accidents, which in turn also makes Lyft more affordable for riders and a better way to earn a living for drivers. The Telematics team acts as a platform team that processes petabytes of mobile sensor data — millisecond-level IMU, gyroscope, and GPS signals — through a series of DAG-based transformations and ML model inferences to detect harsh driving events and convert them into normalized risk features that other Lyft services consume. Our technology stack runs on AWS, Kubernetes, Spark, and Apache Airflow. In this role, you'll work closely with data scientists, actuarial teams, other backend and data engineers, and product management — partnering across geos to build risk-aware products that rank and reward safe drivers, help off-board unsafe ones, notify drivers in real time, and give claims agents the tools to understand exactly what happened in a ride. You'll also be a key technical partner to our insurance team as they optimize coverage costs and provider relationships. If you are a seasoned engineer with a passion for innovation, high-volume data pipelines, microservices, working in cross-disciplinary environments and possess the skills to ensure the ongoing maintenance and improvement of services, you will thrive on our team! You can read about some of the products that Telematics powers in this blog post: https://www.lyft.com/blog/posts/lyfts-impact-on-road-safety Responsibilities: Be a champion of the team's safety and affordability mission, serving as a reliable source of risk insights for teams across Lyft — from driver ranking and safety rewards to accident claims resolution and insurance strategy. Lead medium to large projects, ensuring end-to-end execution with a focus on high quality and reliability. Work cross-functionally with Data Scientists to productionize models that turn raw sensor signals into harsh-event detection and risk features, driving the team's industry-leading innovation in this space. Drive future work to reduce latency, simplify, and improve the accuracy of both our back-end and on-device models that predict accidents before they happen. Actively unblock and support team members, fostering a collaborative and efficient work environment. Take a lead role in the ongoing maintenance of our Telematics systems, reducing tech debt and operating costs through sensible, data-driven design decisions. Collaborate with product management and leadership across geos to define and execute ambitious roadmaps for Telematics. Apply the latest AI tools to boost engineering and business productivity, sharing what you learn with the team. Utilize your expertise in Python, AWS, Spark, SQL (Databricks/Presto), etc. to deliver robust and scalable solutions. Participate in our team's on-call rotations, respond to incidents, and support other teams in mitigating customer-impacting events. Experience: 4+ years of software engineering industry experience Experience in backend software development of large-scale distributed systems Experience and/or interest in running large batch processing jobs with Spark or other large scale compute architectures Experience and/or interest in Library development Experience and/or interest in serving, versioning, monitoring ML models in production environments Experience defining API schemas and developing backend services in a microservices environment Experience with S3, Spark, Presto, Parquet, Databricks You're a great communicator, and can advocate for your proposals while also empathizing with your cross-functional teammates' goals and priorities You collaborate well with a geographically distributed team Benefits: Extended health and dental coverage options, along with life insurance and disability benefits Mental health benefits Family building benefits Child care and pet benefits Access to a Lyft funded Health Care Savings Account RRSP plan with company match to help save for your future In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible. Subsidized commuter benefits and Lyft ride credits Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request. Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process. Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions. This job fills an existing vacancy.

Palo Alto, CA

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. SR. IT DATA ENGINEER At SpaceXSI, the IT Data Engineering team implements and supports applications to help internal customers meet their operational needs. We establish processes for continual improvement, guide administration, and partner with multiple stakeholders on a project-to-project basis. Our mission is to keep the business running effectively while maintaining a healthy application environment. RESPONSIBILITIES: Help lead SpaceXSI's data strategy by implementing established ETL patterns, creating and supporting dependable infrastructure, and reusable components Partner with business and engineering teams to prioritize requests and consistently deliver excellent results against time-sensitive priorities Collaborate effectively in a fast-paced environment using strong interpersonal communication skills BASIC QUALIFICATIONS: Bachelor's degree 5+ years of experience in data engineering roles PREFERRED SKILLS AND EXPERIENCE: Experience working in an enterprise environment Bachelor's degree in computer science Strong experience with databases (Vertica, MySQL, or similar) and advanced SQL Java development experience (Spring, JEE/JSE) and proficiency in Python or other modern languages Hands-on experience with integrations, APIs, and message queuing technologies (e.g., Kafka, RabbitMQ) Experience working with 3rd party APIs (Salesforce, Workday, etc.) Background working in an Agile environment Experience with API Gateways (e.g., Kong), RAML, and REST-based APIs Designing and deploying scalable, reliable, high-volume data integrations and real-time pipelines Big data technologies (Hadoop, MongoDB, HBase, Cassandra) On-prem and cloud enterprise solutions (Oracle, Salesforce, Workday) Scala / Scalding Deep knowledge of access control and data security Leading Data/BI/Analytics projects with a customer-first approach Custom ETL design, implementation, and maintenance Performance monitoring, error logging, and troubleshooting Java applications COMPENSATION AND BENEFITS: $172,000 - $258,000 USD Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice .

Remote - Canada

Data Engineer at Samsara in Remote - Canada focuses on Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction,. Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring.

Remote, Canada; Remote, United States

Backend Engineer, Knowledge Graph (Rust) at GitLab in Remote, Canada; Remote, United States focuses on GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation.

Remote Ireland; Remote, Australia; Remote, Canada; Remote, India; Remote, Mexico; Remote, Poland; Remote, United Kingdom; Remote, United States

Recruiter, R&D at GitLab in Remote Ireland; Remote, Australia; Remote, Canada; Remote, India; Remote, Mexico; Remote, Poland; Remote, United Kingdom; Remote, United States focuses on GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation.

Calgary, Canada; Montréal, Canada; Toronto, Canada

Emerging Enterprise Core Account Executive at Databricks in Calgary, Canada; Montréal, Canada; Toronto, Canada focuses on Emerging Business, Canada | Toronto, ON (Calgary, Vancouver and Montreal considered) About the role As an Emerging Enterprise. These are enterprises and growth companies that are modernizing their data platforms and putting AI from POC to Production.