Senior Data Engineer - Remote

Improve the lives of others while Caring. Connecting. Growing together.

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care’s most complex challenges. Your contributions here have the potential to change lives.

Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together.

As a Senior Data Engineer, you will play a key role in building, optimizing, and maintaining scalable data architectures and pipelines that power critical healthcare data solutions.

Functions include data architecture, engineering, modeling, integration, optimization, security, and development of cloud-based data solutions. The role designs and delivers scalable, reliable, and high-performing data platforms that support business operations, analytics, and applications. Responsibilities include ensuring data quality, governance, traceability, and compliance; automating validation and monitoring; identifying opportunities to improve business processes; and collaborating with business and technology teams. The role also provides technical guidance, establishes engineering best practices, and supports the successful delivery and operation of enterprise data solutions.

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.

• Lead the design and delivery of scalable, governed data engineering solutions, including technical direction, implementation planning, risk management, and production readiness for data products used by business, analytics, and AI/ML stakeholders
• Develop and manage robust ETL/ELT pipelines for data ingestion, transformation, and integration from heterogeneous sources, including relational databases, APIs, file shares, and end-user-computing assets
• Develop Python and PySpark solutions for distributed data processing, automation, integration, and reusable transformation logic
• Optimize data platform performance and cloud consumption through SQL tuning, Spark job optimization, storage format selection, partitioning strategies, cluster configuration, and workload scheduling
• Build and optimize workflows on Azure Cloud services and Databricks — including medallion (bronze/silver/gold) layering and orchestrated pipelines — to support enterprise data needs
• Migrate business logic embedded in legacy and end-user-computing systems into documented, testable transformation logic over governed tables
• Define and implement data quality, validation, reconciliation, and parity testing practices to ensure migrated pipelines are accurate, reliable, auditable, and consistent with the systems they replace
• Establish data lineage, ownership, and cataloguing, and define documented rollup and allocation rules where source systems operate at differing grains
• Implement security and compliance measures for handling PHI/PII and confidential business data in accordance with HIPAA or similar regulations, including de-identification and masking for controlled sharing
• Build and improve CI/CD, version control, and automated testing practices for data pipelines
• Implement monitoring, alerting, logging, and operational runbooks for data pipelines to ensure reliability, timely issue detection, incident response, and continuous improvement of production data platforms
• Support AI/ML and advanced analytical workflows by provisioning trusted data, scalable…