Data Engineer

We're looking for a Data Engineer to join a high-performing, collaborative engineering team focused on building and optimizing the infrastructure that powers our healthcare data platform. In this role, you’ll take ownership of end-to-end data pipelines and play a key part in delivering enterprise-level data solutions that drive real-world impact.
This is a fast-paced environment where your work will directly influence the performance, scalability, and reliability of our data systems—particularly in ingesting and transforming large-scale healthcare datasets. Key Responsibilities

• Design, develop, and maintain scalable ETL pipelines using Python, SQL, and Snowflake
• Build automated, testable, and maintainable data workflows to support core analytics and reporting functions
• Leverage AWS services (e.g., S3, Step Functions, Batch, DynamoDB) to deploy and scale data applications
• Integrate data validation and unit testing into the development process
• Collaborate closely with data scientists, analysts, and engineers to deliver high-quality datasets and APIs
• Work with large healthcare data sources (including claims data) to build efficient and reliable data ingestion processes

What We’re Looking For

• Hands-on experience with ETL pipeline development using Python and SQL
• Strong working knowledge of Snowflake, Pandas, PySpark, and AWS data services
• Proven ability to work with and process large datasets (1GB+) efficiently
• Experience with healthcare data, particularly claims or clinical data, is strongly preferred
• Familiarity with shell scripting for automation and task orchestration
• Detail-oriented mindset with a focus on data quality, validation, and debugging
• Ability to commit to 40 hours per week for a minimum of 6 months