

Gardner Resources Consulting, LLC
Population Health Data Engineer (Epic & Healthcare Analytics)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Population Health Data Engineer (Epic & Healthcare Analytics) on a contract basis, hybrid location (25% onsite), offering $“pay rate” for 6+ years of experience in healthcare data engineering, Epic systems, and modern data tools like Snowflake and DBT.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 6, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Boston, MA
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🧠 - Skills detailed
#Snowflake #Data Engineering #Computer Science #Data Quality #"ETL (Extract #Transform #Load)" #Data Pipeline #Datasets #SQL (Structured Query Language) #Compliance #dbt (data build tool) #Data Modeling #Cloud #Scala #Data Governance
Role description
Population Health Data Engineer (Epic & Healthcare Analytics) - Hybrid
Location: Hybrid (25% onsite / 75% remote)
Openings: 2 positions
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
Population Health Data Engineer (Epic & Healthcare Analytics) - Hybrid
Location: Hybrid (25% onsite / 75% remote)
Openings: 2 positions
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





