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Optum Health Data Engineer Jobs (NOW HIRING)

LMI Consulting, LLC

Health Data Engineer - Mid

Tysons, VA · On-site

$115K - $139K/yr

Health Data Engineer - Mid Job Locations US-VA-Tysons ID 2026-14376 # of Openings 1 Overview LMI is a new breed of digital solutions provider dedicated to accelerating government impact with ...

Guidehouse

Public Health Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Exposure to CI/CD tools and DevOps practices. * AWS, Azure, Databricks, or related cloud/data certifications. * Experience supporting healthcare, public sector, or federal clients. * Interest in data ...

LMI

Health Data Engineer - Mid

Tysons, VA · On-site

$115K - $139K/yr

We are seeking a results-driven Mid-Level Data Engineer to join our team and contribute to developing cutting-edge healthcare data solutions. This role involves building, managing, and optimizing ...

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Optum Health Data Engineer information

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How much do optum health data engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for optum health data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is an Optum Health Data Engineer?

An Optum Health Data Engineer is a technology professional who designs, builds, and maintains data systems for Optum, a health services and innovation company. Their main responsibilities include gathering healthcare data from various sources, ensuring data quality and security, and developing data pipelines to support analytics and reporting. They work closely with data scientists, analysts, and other stakeholders to provide accurate and accessible health data that drives business decisions and improves patient outcomes. Proficiency in tools like SQL, Python, and cloud platforms (such as AWS or Azure) is often required. These engineers play a key role in supporting Optum's mission to improve healthcare delivery through technology and data-driven insights.

What are some common challenges faced by Optum Health Data Engineers when integrating diverse healthcare data sources?

Optum Health Data Engineers often encounter challenges related to integrating data from multiple, disparate healthcare systems, each with unique formats and standards. Ensuring data quality, consistency, and compliance with healthcare regulations like HIPAA adds complexity to the process. Collaborating closely with data scientists, analysts, and healthcare professionals is essential to accurately map data and maintain integrity throughout the data pipeline. Proactively addressing these integration hurdles helps deliver reliable data for advanced analytics and decision-making.

What are the key skills and qualifications needed to thrive as an Optum Health Data Engineer, and why are they important?

To thrive as an Optum Health Data Engineer, you need a solid background in data engineering, SQL, and data warehousing, typically supported by a degree in computer science or a related field. Proficiency with tools such as Python, Spark, ETL platforms, and experience with cloud services like AWS or Azure, along with relevant certifications, is highly valuable. Strong analytical thinking, problem-solving abilities, and effective communication skills make candidates stand out in this role. These competencies are essential for building reliable data solutions that support healthcare analytics, improve patient outcomes, and drive business decisions.

What is the difference between Optum Health Data Engineer vs Optum Health Data Analyst?

AspectOptum Health Data EngineerOptum Health Data Analyst
Primary RoleDesigns, develops, and maintains data pipelines and infrastructureAnalyzes data to generate reports and insights for decision-making
Required SkillsSQL, ETL, data modeling, programming (Python, Spark)SQL, data visualization, statistical analysis
CertificationsTypically data engineering or cloud certifications (e.g., AWS, Azure)Often data analysis or business intelligence certifications
Work EnvironmentData engineering teams, IT infrastructureBusiness units, analytics teams

Optum Health Data Engineers focus on building and maintaining data systems, while Data Analysts interpret data to support business decisions. Both roles require strong SQL skills, but Data Engineers emphasize data pipeline development, whereas Data Analysts focus on data analysis and reporting.

What are popular job titles related to Optum Health Data Engineer jobs?

For Optum Health Data Engineer jobs, the most frequently searched job titles are:

Infographic showing various Optum Health Data Engineer job openings in the United States as of September 2026, with employment types broken down into 95% Full Time, and 5% Part Time. Highlights an 80% In-person, 10% Hybrid, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Population Health Data Engineer

Rex, GA • On-site

Software Technology Inc
See more jobs at Software Technology Incexternal

$106K - $127K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Population Health Data Engineer

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.

Apply