We are seeking a skilled Population Health Data Engineer with deep expertise in Epic data ecosystems and healthcare analytics. This role will focus on designing, building, and optimizing data pipelines and models to support population health, quality of care and claims analytics.
Key Responsibilities- Design, develop, and maintain scalable data pipelines supporting population health, claims analytics, and reporting.
- Work extensively with Epic data sources including Registries, Rosters, Chronicles, Clarity, and Caboodle.
- Integrate clinical and claims data to support longitudinal patient views and advanced analytics.
- Develop data models for population health use cases including quality measures, risk stratification, utilization, and care management analysis.
- Support development and operationalization of risk scoring data models and analytics (e.g., MARA, HCC, RAF).
- Process and transform healthcare claims data (medical and pharmacy) for analytics and reporting.
- Work with Milliman MedInsight data structures to support payer-provider analytics and efficiency benchmarking.
- Build and optimize ELT pipelines using modern cloud platforms.
- Collaborate with healthy planet, efficiency, quality, clinical, and analytics teams to translate business needs into technical solutions.
- Ensure data quality, governance, and compliance with healthcare regulations (e.g., HIPAA).
- Optimize performance of large-scale datasets and queries.
Required Qualifications- Strong hands-on experience with Epic systems, including:
- Epic Registries
- Chronicles data structures
- Hyperspace or Hyperdrive environments
- Clarity and Caboodle data models
- Experience with modern data engineering tools and platforms:
- Snowflake (data warehousing)
- DBT (data transformation and modeling)
- Dynamic Tables in Snowflake
- Solid understanding of healthcare domain concepts, including population health and value-based care.
- Experience with healthcare claims processing (medical and pharmacy claims).
- Hands-on experience with Milliman MedInsight data models and analytics workflows.
- Strong SQL and data modeling expertise.
- Experience building and maintaining data pipelines.
Key Skills- Population Health & Risk Analytics
- Healthcare Data Modeling (Clinical and Claims)
- Epic Data Ecosystem Expertise
- Snowflake & DBT
- SQL & Performance Optimization
- Data Governance & Compliance
Education & Experience- Bachelor's or master's degree in computer science, Health Informatics, Data Engineering, or related field.
- 6+ years of experience in data engineering, with strong preference for healthcare, payer, or population health analytics experience.
