Data Engineer - Healthcare Analytics

Eight Eleven Group
United States
3 days ago
Apply on jobs.eightelevengroup.com
Prepare application

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
$135,200.0 - $176,800.0
Working hours
Regular working hours

Tech stack

Data Analysis Microsoft Azure Business Intelligence Development Big Data Health Informatics Clinical Data Repository Information Systems Information Engineering Extract Transform Load (ETL) Data Systems Data Warehousing Healthcare Effectiveness Data and Information Set
+15 more
Apache Hive Performance Tuning Power BI SQL Databases Tableau (Software) Azure Data Factory Sql Optimization Git Data Lakes Pyspark Information Technology Performance Monitor Drilldown Epic Caboodle Databricks

Job description

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., * 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

Requirements

  • 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

Benefits & conditions

Eight Eleven Group offers competitive medical, dental, vision, Health Savings Account, Dependent Care FSA, and supplemental coverage with plans that can fit each employee’s needs. We offer a 401k plan that includes a company match and is fully vested after you become eligible, paid time off, sick time, and paid company holidays. We also offer an Employee Assistance Program (EAP) that provides services like virtual counseling, financial services, legal services, life coaching, etc.

About the company

Disclaimer: Brooksource, Medasource, and Calculated Hire are part of the Eight Eleven Group family of companies and operate under Eight Eleven Group, LLC. All employees receive the same benefits, policies, and terms of employment.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on jobs.eightelevengroup.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:28 min

Defining big data and machine learning fundamentals

Ayon Roy · LIVE

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

4:32 min

Harnessing Spark with Python using PySpark and Py4J

Ayon Roy · LIVE

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

2:10 min

Why organizations combine big data and machine learning

Ayon Roy · LIVE

3:37 min

Scaling machine learning pipelines from prototypes to petabytes

Julian Joseph · LIVE

Videos

See all

Related articles

See all