Senior Data Engineering Analyst Python AI ML

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.

This role focuses on designing, building, and optimizing secure, scalable data pipelines and analytics capabilities to support enterprise AI initiatives - especially Defensive AI and cross-functional automation programs.

Schedule: 11:00 AM - 08:30 PM

The selected candidate will work across enterprise datasets, AI workflows, and cloud data platforms to enable:

• High-quality data ingestion for model development
• Secure and resilient data processing
• Integration of analytics for platform engineering
• Automation initiatives such as anomaly detection, fraud insights, and AI-ready datasets

• Data Engineering and ETL
• Build and optimize ETL or ELT pipelines using Python (high priority)
• Work with SQL Server and relational databases for data transformations and reporting
• Implement data quality validation and monitoring
• AI/ML Data Enablement
• Prepare training-ready datasets for GenAI, LLMs, and ML models
• Work with model feature extraction pipelines
• Collaborate with data scientists and platform engineers in Defensive AI teams
• Cloud or Platform Engineering
• Build pipelines on cloud data ecosystems (Azure or Databricks or Big Data platforms as applicable internally - supported by DTA job family descriptions)
• Implement secure data processing aligned with enterprise governance
• Cross-Functional Collaboration
• Partner with AI, Data Science, and product teams to finalize datasets
• Support automation and platform integration initiatives across the enterprise
• Python for ETL, data transformation, and automation
• SQL or SQL Server for querying, data modeling, and optimization
• Data Modeling and Data Warehousing - aligns with DTA job architecture
• GenAI or LLM data preparation
• ETL or ELT Development, especially on cloud
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, or related field.
• 5+ years of experience in Data Engineering roles
• Proven experience with Python, SQL, ETL pipelines, and cloud data platforms
• Experience working with large datasets and data quality frameworks
• Experience with Git, CI/CD, and Agile practices
• Experience building secure and scalable data ingestion frameworks
• Exposure to AI, GenAI, LLM-based data preparation, or ML-ready dataset creation
• Familiarity with AI/ML model lifecycle
• Exposure to Databricks or Spark or Big Data
• Solid understanding of data warehousing, modeling, and database design
• Demonstrated ability to collaborate with cross-functional AI, Engineering, and Product teams