Senior Data Engineer - Remote

UnitedHealth Group•Eden Prairie, MN

1d•$91,700 - $163,700•Remote

About The Position

The Optum Health Financial Tech team is seeking a Senior Data Engineer to support Employer & Individual (E&I) HEDIS Retrospective data processing and cloud modernization initiatives. This hands-on technical role will design, develop, and support scalable cloud-based data engineering solutions that enable healthcare quality reporting, operational excellence, and regulatory compliance. The ideal candidate combines solid healthcare and HEDIS domain expertise with modern data engineering skills and experience implementing AI-enabled solutions. You will work closely with business partners, product teams, functional subject matter experts, and auditors to deliver reliable data pipelines, automate workflows, and support critical business commitments across Medicare, Medicaid, and Commercial lines of business. This role requires a solid individual contributor who can influence technical direction, solve complex data challenges, and drive operational excellence in a highly regulated environment. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Requirements

5+ years of experience in the health insurance industry supporting HEDIS programs, healthcare analytics, quality reporting, or healthcare data engineering initiatives
5+ years of experience working with HEDIS concepts, quality measures, measure engines, and healthcare data domains including Member, Eligibility, Medical, Pharmacy (Rx), and Clinical data across Medicare, Medicaid, and Commercial lines of business
5+ years of experience utilizing on-premise or cloud-based SQL databases in a business, research, healthcare, or analytical environment
3+ years of experience designing, developing, and supporting cloud-based data engineering solutions, automated data pipelines, and large-scale data processing workflows
3+ years of Agile/Kanban delivery experience, including engineering best practices such as unit testing, TDD, CI/CD, automated testing, and code reviews
1+ years of experience evaluating, implementing, or deploying AI, GenAI, Agentic AI, or intelligent automation capabilities within enterprise technical workflows
Experience collaborating directly with business stakeholders, auditors, product teams, and technical partners to deliver solutions and resolve issues
Proven experience supporting regulatory compliance reporting, business SLAs, and operational commitments within a regulated healthcare environment
Demonstrated ability to troubleshoot complex technical and data-quality issues and drive effective resolution
Demonstrated ability to communicate complex technical and methodological concepts to non-technical business partners

Nice To Haves

Bachelor's degree in Computer Science, Data Engineering, Health Informatics, Information Systems, or a related technical field (or equivalent experience)
Experience supporting cloud migration initiatives for large-scale healthcare data processing platforms
Experience building and integrating production-ready AI capabilities into cloud-based data engineering architectures and workflows
Experience with Fast Healthcare Interoperability Resources (FHIR) standards and clinical data integrations
Experience supporting NCQA reporting processes and quality-measure implementations
Experience with Databricks, Azure cloud technologies, and modern healthcare data platforms
Experience mentoring engineers and providing technical leadership across cross-functional teams

Responsibilities

Design, develop, test, deploy, and support scalable cloud-based data engineering solutions and automated data pipelines
Develop and optimize data integration frameworks, ETL processes, data transformations, and SQL-based solutions supporting healthcare analytics and HEDIS reporting
Implement enterprise-approved AI, GenAI, and Agentic AI capabilities to automate data engineering workflows, improve operational efficiency, and enhance data quality
Analyze complex business requirements and translate them into scalable technical solutions
Support HEDIS measure processing, quality reporting initiatives, regulatory compliance requirements, and operational service-level commitments
Collaborate with business stakeholders, product teams, auditors, and functional subject matter experts to resolve technical issues, validate data quality, and ensure successful delivery
Investigate production issues, perform root-cause analysis, and implement sustainable corrective actions
Apply engineering best practices including CI/CD, automated testing, code reviews, version control, and quality assurance processes
Contribute to cloud migration initiatives and modernization efforts across healthcare data platforms
Ensure data governance, security, auditability, and regulatory requirements are incorporated into technical solutions
Monitor and optimize data pipeline performance, reliability, scalability, and operational effectiveness
Provide technical guidance and mentorship to other engineers while serving as a senior individual contributor