Principal Data Engineering - Remote

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

Job Description
- Principal Data Engineering
- Remote (2395658)

Principal Data Engineering
- Remote - 2395658

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 in making healthcare work better for everyone through people‑led, responsible AI while Caring. Connecting. Growing together.

The Principal Data Engineer is a senior individual contributor responsible for designing, building, and scaling enterprise data platforms and data pipelines. This role combines cloud‑based data architecture ownership with hands‑on technical execution across cloud and hybrid environments to support large‑scale data, analytics, and machine learning initiatives. Working within Optum Technology, you will partner across engineering, BI, and product teams to ensure high data reliability, performance, and security.

You will also leverage enterprise‑approved AI tools and modern data platforms (Databricks, Snowflake, GCP/Azure/AWS) to automate workflows, optimize pipelines, and drive continuous platform innovation.

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 implementation of cloud‑based and hybrid data architectures, platforms, and enterprise data solutions
• Build, optimize, and maintain scalable ELT/ETL data pipelines utilizing Python, SQL, Spark/PySpark, and modern data platforms (e.g., Databricks, Snowflake)
• Design, develop, and deploy AI‑powered solutions and automated data engineering workflows to address complex business challenges with an emphasis on responsible AI practices
• Design and operationalize ML pipelines in partnership with Data Science, covering feature engineering, training and inference data flows, model versioning, and automated retraining or scoring workflows
• Leverage enterprise‑approved AI tools to streamline technical workflows, automate data tasks, and drive continuous platform improvement
• Evaluate emerging data engineering trends, cloud technologies, and AI capabilities to inform solution design and strategic innovation
• Partner with Analytics/BI, Data Science, and Product teams to deliver trustworthy, high‑performing datasets and metric frameworks
• Ensure data quality, observability, lineage, and documentation across data pipelines using tools like dbt, Great Expectations, and cloud logging/monitoring
• Implement security, IAM, encryption, PII handling, and regulatory compliance controls across all data storage and pipeline layers
• Provide hands‑on technical leadership, solution design reviews, and mentorship to junior and senior engineers
• Troubleshoot and resolve complex data pipeline incidents, driving root cause analysis and preventive platform enhancements

You’ll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

• 7+ years of experience in data engineering, enterprise data platform development, or data architecture roles
• 5+ years of hands‑on experience building and optimizing scalable ELT/ETL data…