Data Engineer

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, and data they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits, and career development opportunities.

Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together.

You'll enjoy the flexibility to telecommute
* from anywhere within the U.S. as you take on some tough challenges.

As a Data Engineer on the team at Optum Technology, you will be responsible for architecting, building, and maintaining high-performance ETL/ELT data pipelines to establish a unified, reliable data foundation for advanced analytics and enterprise reporting. In this role, you will integrate data across on-premises and cloud environments using Snowflake, Apache Airflow, Python, and SQL. You will implement robust data quality, de-identification, and data masking controls, automate CI/CD deployments using Git Hub Actions, and collaborate with Agile teams to solve complex data challenges.

• Design, build, and maintain enterprise ETL/ELT data pipelines integrating data from on-premises and cloud platforms into unified data repositories using Snowflake and Apache Airflow
• Develop complex data transformation routines, SQL stored procedures, and Python scripts to clean, normalize, and aggregate high-volume datasets
• Implement data de-identification, row-level security, and data masking mechanisms in accordance with enterprise data governance standards
• Establish automated data quality validation, monitoring, and error-handling routines using tools such as Great Expectations or Soda
• Create logical and physical data models (e.g., dimensional modeling, star schemas, Data Vault) to optimize analytics performance and data integrity
• Support CI/CD pipeline automation and deployment for data engineering workflows using Git and Git Hub Actions
• Optimize data pipeline performance, query execution times, and resource utilization in cloud data platforms
• Collaborate within Agile/Scrum cross-functional teams to translate business requirements into scalable technical data architectures
• Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI

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.

• 3+ years Proven hands‑on experience in a Data Engineer role building scalable ETL/ELT data pipelines
• 2+ years’ Experience with Azure cloud services (Blob Storage, Azure Data Factory, Azure Functions, Key Vault) or Databricks
• 2+ Experience with version control and CI/CD deployment pipelines using Git and Git Hub Actions
• 1+ Proficiency in Python for data processing, scripting, and pipeline automation

• Bachelor's degree or higher in Computer Science, Information Technology, Database Management, or a related field
• In-depth knowledge of Snowflake architecture, performance tuning, data masking, and access control policies
• Experience orchestrating Airflow data tasks to run on Kubernetes and creating Docker containers
• Strong understanding of data modeling techniques (e.g., Star Schema, Dimensional Modeling, Data Vault) and data warehousing principles
• Experience using data quality frameworks such as Great Expectations…