Principal Data Engineering - Remote

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. As a Principal Data Engineer within the Enterprise Data & Analytics organization under the Chief Data Office, you will serve as a technical subject matter expert leading the architectural design, implementation, and optimization of scalable enterprise data solutions. In this role, you will partner closely with product owners, business stakeholders, and analytics teams to engineer reliable, end-to-end data pipelines across staging, integration, and consumption layers using technologies such as Azure Data Factory, Snowflake, DBT, Python, and metadata-driven frameworks. You will leverage approved AI tools to streamline routine engineering tasks and elevate operational efficiency, while mentoring engineering staff, establishing engineering best practices, and driving continuous technical innovation. You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges.

Collaborate closely with product owners, business users, and stakeholders to translate data product and reporting requirements into scalable, reliable data engineering solutions, incorporating feedback iteratively throughout the delivery lifecycle Design, develop, and maintain end-to-end data pipelines across staging, integration, and consumption layers, leveraging Azure Data Factory, DBT, Snowflake SQL, and metadata-driven frameworks Develop and optimize high-performance SQL queries, views, and stored procedures to support analytics and reporting, and provide guidance to analytics team members on effective and cost-efficient usage Architect, develop, and support data integration processes including batch file ingestion and automated extracts Partner with internal stakeholders to understand business objectives, study requirements, and identify appropriate technical solutions, integration patterns, and data models that balance performance, scalability, and maintainability Serve as a technical subject matter expert and mentor, providing training, design guidance, and code reviews for associates on data engineering best practices, Snowflake optimization, and ADF/DBT pipeline design Author and maintain detailed technical documentation, including data mappings, record layouts, file specifications, interface contracts, workflow diagrams, and operational runbooks for data loads and extracts Continuously evaluate and improve data quality, monitoring, and operational efficiencies Collaborate with business and technical partners to support data acquisition initiatives, including onboarding new data sources, developing business justifications, and executing secure, compliant data transfers Communicate complex technical concepts clearly through written documentation, presentations, and discussions with audiences ranging from technical teams to senior leadership Foster a collaborative, inclusive environment that promotes knowledge sharing, continuous improvement, and professional development across the team Demonstrate strong analytical and troubleshooting skills to diagnose pipeline failures, data anomalies, and performance bottlenecks Utilize enterprise-approved AI tools to streamline workflows, automate repetitive tasks, and increase overall engineering productivity Evaluate emerging tech trends to inform continuous improvement, strategic innovation, and efficient solution design You'll be rewarded and recognized for your