Sr. Staff Engineer, Data Engineering

About the role

Please note, this team is hiring across all levels and candidates are individually assessed and appropriately leveled based upon their skills and experience.

We are seeking skilled engineers to build scalable distributed systems and integrate agentic AI and conversational analytics. As a Senior Staff Engineer, you will lead the architecture, data modeling, and core infrastructure powering our next-generation AI and analytics platforms.

Role and Responsibilities

• Architect, develop, and deploy global-scale distributed platforms and pipelines for massive data ingestion, transformation, and analytical reporting.
• Design and refine backend infrastructure supporting Agentic AI workflows, autonomous systems, and conversational analytics with natural language interfaces.
• Partner with application teams to define data strategies and durable conceptual models spanning OLTP/OLAP and generative AI architectures (e.g., RAG).
• Evaluate data integration challenges and deliver optimized architectural solutions for complex business requirements.
• Research emerging AI techniques and advanced machine learning methodologies to continuously enhance data design patterns.
• Provide technical leadership and mentorship across the project lifecycle, focusing on efficient data modeling, prompt engineering, and high-performance data access services.

Qualifications

• At least 8 years of hands-on experience in architecture, design, or development of enterprise data solutions, applications, and integrations.
• Proven experience designing and deploying Agentic AI systems and working with AI application frameworks.
• Strong communication, presentation, and interpersonal skills with the ability to articulate complex concepts clearly.
• Bachelor or Master degree in STEM majors.
• Strong algorithms, data structures, and coding background with either Java, Python, or Scala programming experience (Python highly preferred for AI/ML ecosystem compatibility).
• Exceptional proficiency in SQL, alongside familiarity with semantic search and Natural Language to SQL paradigms.
• Experience building products using at least 1 of each of the following distributed technologies:
  - Relational Stores (i.e. Postgres, MySQL, or Oracle)
  - Columnar, NoSQL, or Vector Stores (i.e. Starrocks, Clickhouse, BigQuery, Pinecone or pgvector)
  - Distributed Processing Engines (i.e. Apache Spark, Apache Flink)
  - Distributed Queues (i.e. Apache Kafka, AWS Kinesis, or GCP PubSub)
• Experience with software engineering standard methodologies (e.g., unit testing, code reviews, design documents).
• Experience working with GCP, Azure, AWS, or similar cloud platform technologies.