Join Optum, a global leader dedicated to improving health outcomes through technology. We are seeking a Senior Data Engineering Analyst to contribute to our mission of advancing health optimization worldwide.

As part of our inclusive culture, you'll collaborate with talented peers, leverage comprehensive benefits, and access career development opportunities. Our work directly impacts millions by connecting individuals with essential care, pharmacy benefits, data, and resources.

Embrace our values of Caring, Connecting, and Growing Together as we make a significant impact on the communities we serve.

Key responsibilities include designing and implementing scalable ETL/ELT pipelines for diverse data sources, developing cloud-native solutions on platforms like Databricks and Snowflake, and applying data modeling techniques to create analytics-ready datasets.

You will ensure data quality, reliability, and auditability, adhering to enterprise data governance and security standards. Optimization of data workloads for performance and cost efficiency is crucial.

This role involves supporting legacy system modernization, partnering with stakeholders to translate requirements into production-grade solutions, and enabling downstream analytics and AI/ML initiatives. Applying software engineering best practices, including CI/CD and code reviews, is essential. You will also contribute to architectural discussions, mentor junior engineers, and design/deploy AI-powered solutions responsibly.

A Bachelor's degree in Computer Science or a related engineering field is required, coupled with a minimum of 5 years of experience in Data Engineering or data platform/analytics engineering roles.

Proficiency is expected in SQL, data modeling, and data transformations (3+ years). Significant hands-on experience with Databricks and/or Snowflake for large-scale data processing is necessary (3+ years).

Experience in building ETL/ELT pipelines, data warehouses, and analytical data stores is required (3+ years), along with experience in source control and DevOps practices (3+ years).

Preferred qualifications include experience with enterprise-scale data platforms, real-time streaming frameworks, and GenAI tools. A strong understanding of secure coding practices and the ability to troubleshoot and optimize large-scale pipelines are also highly valued.