About the Role
We’re looking for an experienced data engineering professional to join us in our mission to eliminate the financial complexity of healthcare. You'll join our Data Science Engineering team to own the data lifecycle of healthcare claims data including ELT/ETL, de-identification, PHI/PII reduction, data quality, observability, and integrations.
Responsibilities
- Build and maintain reliable data pipelines that process raw claims data from diverse sources to enriched, standardized formats using tools including Python, SQL, PostgreSQL, Trino, ClickHouse, Airflow, Datadog, and AWS cloud services
- Build automated observability and monitoring into data quality
- Produce privacy-preserving datasets and protect PHI, implementing de-identification and PII-reduction specifications
- Draft technical design and documentation
- Seek and prioritize technical and product feedback from internal customers
- Iterate quickly with an eye towards value
What you’ll bring to the role
- 4+ years developing data models, pipelines, and end-to-end analytical solutions
- Programming experience in Python and SQL
- Experience with healthcare claims data (e.g., EDI 837/835 files, CMS datasets, or commercial claims)
- Advanced SQL including window functions, subqueries, CTEs, performance tuning and indexes
- Data modeling experience in support of diverse OLAP and OLTP workflows
- Comfortable with object-oriented and functional programming patterns and debugging workflows
- Experience with ETL/ELT workflows, orchestration (e.g., Airflow), and data engineering patterns
- Ability to design data systems with scalability, performance, and cost efficiency in mind
- Software engineering rigor including automated testing and version control
Bonus points
- Experience with revenue cycle and healthcare payments or payer-provider contracting
- Experience handling sensitive data in a regulated environment
- Experience with cloud services (AWS S3, EC2, RDS)
- Leadership experience acting as both a player and a coach