Data Engineer - Healthcare Analytics
Remote
This is a Remote role.
Compensation: $65 - $85 per hour
Contract Length: Up to 12 months
Hours: 8am-5pm MST, M-F
Start Date: ASAP, 10/5/2026
ABOUT THE ROLE
Join a mission-driven healthcare analytics team supporting a nonprofit health insurance provider serving over 1 million members across the Mountain West region. As a Data Engineer, you will play a key role in building the data foundation for value-based care initiatives, including risk adjustment, quality metrics (Stars and HEDIS), and medical expense management. This contract position is fully remote and offers the opportunity to design and implement data models and pipelines in Azure Databricks, powering executive-level Joint Operating Committee (JOC) dashboards and provider-facing performance views. You will collaborate closely with BI developers and analytics leaders in a fast-paced, highly iterative environment focused on delivering actionable insights for both internal and external stakeholders.
WHAT YOU'LL DO
Design and implement robust data models and pipelines in Azure Databricks to support healthcare analytics and value-based care initiatives
Develop and maintain ETL/ELT processes with a focus on data quality, consistency, lineage, and performance for BI and analytics consumption
Build and optimize Delta Lake medallion architecture (bronze/silver/gold layers) for scalable, high-performance data solutions
Collaborate daily with BI developers, analytics leaders, and stakeholders to deliver executive-level Joint Operating Committee (JOC) dashboards and provider-facing performance views
Integrate and analyze healthcare payer data, including claims, encounter, medical expense, MLR, cost-of-care, quality metrics (Stars, HEDIS), and risk adjustment (Medicare Advantage HCC, HHS-HCC)
Design analytic models and hierarchies supporting both executive-level and provider-level reporting and drill-down capabilities
Orchestrate data workflows using Databricks Workflows and/or Azure Data Factory
Communicate technical concepts and modeling decisions clearly to non-technical analytics leaders and stakeholders
Adapt to changing requirements, participate in daily standups, and engage in direct client interaction in a fast-paced, iterative environment
Leverage advanced SQL, Spark SQL, and PySpark for complex data engineering tasks
WHAT YOU BRING
7+ years as a Data Engineer or similar, working with large, complex datasets
3+ years hands-on experience with Azure Databricks, including production-level PySpark and Spark SQL (beyond notebook-only or SQL-only usage)
Expertise with Delta Lake and medallion (bronze/silver/gold) architecture
Advanced SQL and dimensional data modeling skills; able to design gold/serving layers for direct BI consumption
Experience orchestrating data workflows with Databricks Workflows and/or Azure Data Factory
Proven healthcare payer data experience, including claims, encounter data, medical expense, MLR, cost-of-care, quality metrics (Stars, HEDIS), and risk adjustment (Medicare Advantage HCC, HHS-HCC)
Experience designing analytic models and hierarchies for both executive and provider-level reporting and drill-down
Robust ETL/ELT pipeline development with a focus on data quality, consistency, lineage, and performance
Comfortable with changing requirements, daily standups, and direct client interaction
Strong communication skills; able to explain modeling decisions to non-technical stakeholders
Bachelor's degree in Computer Science, Information Systems, Data/Analytics, Statistics, or related field, or equivalent experience
Preferred: Databricks (Data Engineer Associate or Professional) and Microsoft Azure data/analytics certifications
Preferred: Experience with Unity Catalog, dbt, and Git-based CI/CD for data
Preferred: Experience with Epic-sourced data (Caboodle, Clarity) or other clinical data platforms
Preferred: Prior value-based care or population health analytics experience
Preferred: Familiarity with Power BI and/or Tableau for data modeling and performance optimization
Preferred: Experience building datasets for both internal payer teams and external provider organizations from a shared model
Preferred: Exposure to JOC or executive-level healthcare performance reporting
Preferred: Experience with enterprise measure engines (Inovalon, Cotiviti, Optum, Edifecs, Milliman MedInsight) or custom measure logic