Join Optum, a global leader in health technology, and contribute to improving health outcomes for millions. Our mission is to connect individuals with the care, pharmacy benefits, data, and resources they need for optimal well-being. We foster an inclusive culture where talented professionals thrive, with comprehensive benefits and opportunities for career growth. Advance health optimization on a global scale by joining our team and embracing our values of Caring, Connecting, and Growing together.

This role focuses on enhancing identity data integration and analytics, ensuring the accuracy, consistency, and security of identity-related information across the enterprise.

Design and implement robust, scalable data pipelines and identity data integration solutions. Develop frameworks for data validation, cleansing, reconciliation, and governance to ensure data integrity. Optimize data models, data lakes, and warehouse structures for advanced identity analytics, access reviews, and compliance reporting. Build and deploy solutions using Azure Data Factory, Databricks, SQL, Spark, or similar cloud technologies. Automate data workflows, enhance ETL/ELT processes, and improve pipeline reliability and monitoring. Ensure all data engineering solutions adhere to stringent security standards, privacy regulations, and enterprise IAM policies. Collaborate closely with IDM architects, security experts, application owners, and business stakeholders to define data requirements and deliver impactful identity data solutions. Adhere to all company policies, procedures, and business directives, including those related to work arrangements and assignments.

A minimum of 7.5 years of dedicated experience in Data Engineering is required. Demonstrated hands-on expertise with cloud data platforms such as Azure Data Factory and Databricks, or comparable cloud environments. Proficiency in Generative AI technologies including OpenAI, Claude, Gemini, LangChain, Agents, RAG, Vector Databases, Prompt Engineering, and fine-tuning is essential. Solid experience with data governance, data quality, and metadata management frameworks. Strong foundational skills in SQL, Python, PySpark, and ETL/ELT development are crucial for success in this role.