Join Optum, a global leader in healthcare technology, and contribute to improving health outcomes for millions. We are seeking a skilled Data Engineer to design, build, and operate scalable data solutions on modern cloud platforms. This role offers a dynamic work environment with talented peers, comprehensive benefits, and opportunities for career growth within a culture that values inclusion and community impact. Advance health optimization on a global scale and be part of an organization dedicated to Caring, Connecting, and Growing together.

This position involves developing innovative, cloud-native data solutions and enabling downstream analytics, reporting, and AI/ML workloads. You'll have the chance to apply software engineering best practices and contribute to architectural discussions, fostering a collaborative and forward-thinking team atmosphere.

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 ensuring data quality and reliability. You will apply data modeling techniques to create analytics-ready datasets and optimize data workloads for performance and cost-efficiency.

This role also involves partnering with stakeholders to translate requirements into production-grade data solutions, supporting legacy pipeline modernization to cloud-native architectures, and applying software engineering best practices like CI/CD and code reviews. Additionally, you will contribute to architectural discussions, mentor junior engineers, and design AI-powered solutions responsibly.

We require a Bachelor's degree in Computer Science or a related engineering field, along with at least 5 years of experience as a Data Engineer or in analytics engineering roles. Essential technical skills include 3+ years of experience with SQL, data modeling, and data transformations.

Proficiency in Databricks and/or Snowflake for large-scale data processing is crucial, as is 3+ years of experience building ETL/ELT pipelines, data warehouses, and analytical data stores. Familiarity with source control and DevOps practices, including Azure DevOps and CI/CD, is also a requirement for this position. Experience with enterprise-scale data platforms and real-time/streaming frameworks is preferred.