Population Health Data Engineer (Epic & Healthcare Analytics)

Job

Gardner Resources Consulting, LLC

Remote

Full-Time

Posted 2 weeks ago (Updated 2 weeks ago) • Actively hiring

Expires 6/15/2026

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Job Description

Population Health Data Engineer (Epic & Healthcare Analytics) -

Hybrid Location:

Hybrid (25% onsite / 75% remote)

Travel:

Project-based (typically once per quarter + Go-Live in Q4)

Employment Type:

Contract with potential for conversion or extension Overview We are seeking two skilled Population Health Data Engineers with deep expertise in Epic data ecosystems and healthcare analytics. This role focuses on designing, building, and optimizing data pipelines and data models to support population health initiatives, 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 records and advanced analytics Develop data models for population health use cases (quality measures, risk stratification, utilization, care management) Support development and operationalization of risk scoring models (e.g., MARA, HCC, RAF) Process and transform healthcare claims data (medical and pharmacy) for analytics and reporting Leverage Milliman MedInsight data structures for payer-provider analytics and benchmarking Build and optimize ELT pipelines using modern cloud platforms Collaborate with clinical, quality, population health, and analytics teams to translate business needs into technical solutions Ensure data quality, governance, and compliance (e.g., HIPAA) Optimize performance of large-scale datasets and queries Required Qualifications Strong hands-on experience with Epic systems, including: Registries Chronicles data structures Hyperspace or Hyperdrive environments Clarity and Caboodle data models Experience with modern data engineering tools: Snowflake (data warehousing) DBT (data transformation/modeling) Dynamic Tables in Snowflake Strong SQL and data modeling expertise Experience building and maintaining scalable data pipelines Solid understanding of population health and value-based care concepts Experience with healthcare claims data (medical and pharmacy) Hands-on experience with Milliman MedInsight Key Skills Population Health & Risk Analytics Healthcare Data Modeling (clinical + 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 data engineering experience, preferably in healthcare, payer, or population health analytics