Senior Healthcare Data Engineer

Milliman is a leading firm in the healthcare sector, seeking an experienced data professional for their Seattle Health Practice. The Senior Healthcare Data Engineer will develop and maintain data pipelines for processing healthcare claims and enrollment data, ensuring analytic accuracy and contributing to the improvement of analytic codebases and data products.

Responsibilities:

• Develop and maintain data pipelines that process healthcare claims, enrollment, and related administrative data
• Own components of data pipelines end-to-end, from raw data processing through final analytic outputs
• Translate technical specifications and business rules into well-structured, maintainable code
• Work with large-scale healthcare datasets (tens to hundreds of millions of rows) within the VRDC's secure computing environment
• Perform data validation, quality checks, and reconciliation to ensure analytic accuracy
• Identify opportunities to improve code quality, reduce duplication, and strengthen testing, validation, and documentation
• Ensure reproducibility and traceability of results across data refreshes and measurement years
• Communicate technical findings, methodology, and data issues clearly to actuarial and consulting staff
• Manage concurrent workstreams across multiple measurement years and data refresh cycles

Requirements:

• 10+ years of professional experience in data engineering, analytics, or a quantitative analyst role with substantial hands-on coding
• Healthcare data experience — Medicare/Medicaid/commercial claims, enrollment files, pharmacy data, or similar
• Strong SQL proficiency — complex joins, window functions, conditional aggregation, and careful handling of NULLs and edge cases
• Programming experience in Python, SAS, or both; willingness to work across languages as needed
• Experience processing large datasets and an understanding of performance considerations at scale
• Experience implementing business logic from technical specifications
• Familiarity with data modeling and structuring large analytical datasets for reuse
• Demonstrated ability to learn complex domains and business rules quickly
• Strong written and verbal communication skills
• A genuine interest in code quality — you think about naming, structure, validation, and maintainability
• Familiarity with healthcare quality measures, such as HEDIS, PQA and CAHPS
• Experience with Databricks, PySpark, or distributed data processing frameworks
• Git-based version control and collaborative development workflows
• Experience working within the CMS CCW/VRDC or comparable restricted research data environments
• Experience with agentic AI coding tools such as Cursor, Copilot, Codex, or Claude Code
• Background in healthcare consulting or health plan analytics