The Data Engineer designs, develops, and optimizes complex ETL pipelines, data models, and Python scripts for data ingestion and automation. Responsibilities include managing data workflows with Apache Airflow, collaborating with data stakeholders, ensuring data security, and mentoring junior team members. Candidates require a bachelor's degree in computer science or a related field and at least four years of hands-on data engineering experience.
Join a leading U.S.-based technology platform for the life insurance and annuities industry. Through innovative enterprise solutions and data-driven insights, the company simplifies how insurance products are bought, sold, and administered, helping millions of people protect their financial futures.
With a bold, collaborative, and value-driven culture, the company manages hundreds of billions of dollars in assets under administration and partners with more than 100 insurance carriers and thousands of distributors across the market.
Responsibilities
- Design, develop, and optimize complex ETL pipelines that integrate large data sets from various sources.
- Build and maintain high-performance data models using Google BigQuery/ Snowflake and DBT for data transformation.
- Develop Python scripts for data ingestion, transformation, and automation.
- Implement and manage data workflows using Apache Airflow for scheduling and orchestration.
- Collaborate with data scientists, analysts, and other stakeholders to ensure data availability, reliability, and performance.
- Troubleshoot and optimize data systems, identify issues, and resolve them proactively.
- Work on cloud-based platforms, particularly AWS, to leverage scalability and storage options for data pipelines.
- Ensure data integrity, consistency, and security across systems.
- Take ownership of end-to-end data engineering tasks while mentoring junior team members.
- Continuously improve processes and technologies for more efficient data processing and delivery.
- Act as a key contributor to developing and supporting complex data architectures.
Requirements
- Bachelor’s degree in computer science, Information Technology, or related field.
- 4+ years of hands-on experience in Data Engineering or related fields, with a strong background in building and optimizing data pipelines
- Strong proficiency in Google Big Query, including designing and optimizing queries or other equivalent Datawarehouse (Snowflake).
- Knowledge of dbt for data transformation and model management.
- Proficiency in Python for data engineering tasks, including scripting, data manipulation, and automation.
- Solid experience with Apache Airflow for workflow orchestration and task automation.
- Extensive experience in building and maintaining ETL pipelines.
- Familiarity with cloud platforms, particularly AWS (Amazon Web Services), including tools like S3, Lambda, Redshift, or Glue.
- Excellent problem-solving and troubleshooting abilities.
- Strong communication and collaboration skills with the ability to work effectively in a team environment.
- Self-motivated, detail-oriented, and able to work with minimal supervision.
- Ability to manage multiple priorities and deadlines in a fast-paced environment.
- Experience with other cloud platforms (e.g., AWS, Azure) is a plus.
- Knowledge of data warehousing best practices and architecture.
Benefits
- Your pick when it comes to employment models: CLT/PJ/Cooperativa;
- We provide resources for you to grow and learn on the job, including online courses, mentoring, and the latest gen laptops;
- A fully remote work environment with flexible working hours;
- Bonus for any referrals that we end up hiring;
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