Senior Data Engineer
About The Position
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. You’ll enjoy the flexibility to telecommute from anywhere within the U.S. as you take on some tough challenges.
Requirements
- Bachelor's degree or equivalent experience
- 6+ years of experience in analytics engineering, business intelligence, or data engineering roles delivering enterprise-scale analytics solutions
- 5+ years of Cloud experience (Azure, GCP, AWS, or OCI)
- 5+ years of experience in programming languages such as Python, Java, etc.
- 4+ years of hands-on experience using Databricks (Spark, SQL, Python, notebooks) or other major ETL platforms to build and optimize large-scale data pipelines
- 4+ years of experience in data modeling (star schemas, semantic modeling, incremental loads, large datasets) and advanced SQL
- 1+ years of experience delivering AI-driven analytics or data solutions
Nice To Haves
- Healthcare industry experience, specifically in clinical or real-time analytics
- Experience with ETL orchestration tools (e.g., Airflow, Azure Data Factory) and managing data lineage in governed environments
- Experience developing AI-driven automations or integrating large language models (LLMs) into data products and ETL workflows
- Experience with Power BI, Tableau or other visualization tools, including advanced DAX, Power Query, and semantic modeling
- Demonstrated experience working in global delivery models with effective onshore-offshore collaboration
- Proven ability to solve complex technical problems with a focus on data processing efficiency and system scalability
Responsibilities
- Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on the responsible use of AI
- Architect and optimize complex ETL processes and data pipelines using Databricks (Spark, SQL, Python) or other enterprise-scale integration tools to ensure high-performance processing of large-scale datasets
- Evaluate emerging trends in ETL frameworks and AI to inform solution design and drive strategic innovation within the analytics platform
- Use enterprise-approved AI tools to automate data engineering workflows, streamline ETL maintenance, and drive continuous improvement in engineering velocity
- Implement advanced data modeling techniques, such as star schemas and incremental loads, to ensure data integrity and scalability across all ETL layers
- Build and maintain executive-level dashboards and semantic models in Power BI, ensuring seamless data flow from backend ETL processes to end-user visualizations
- Partner with product and business leaders to translate complex business requirements into robust, automated data integration solutions
- Lead technical coordination within a global delivery model, ensuring consistency and quality of ETL standards across onshore and offshore teams
- Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI
Benefits
- comprehensive benefits package
- incentive and recognition programs
- equity stock purchase
- 401k contribution
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Associate degree
