Join Optum, a global leader in health optimization, and contribute to improving health outcomes through innovative technology. We foster an inclusive culture where talented individuals can grow their careers and make a significant impact.

Advance health optimization on a global scale by joining our team. Embrace a culture of Caring, Connecting, and Growing together as you help millions live healthier lives. Your work will directly connect people with the care, resources, and data they need.

As a Data Engineering Lead, you will be instrumental in designing and implementing robust data pipelines and identity data integration solutions. Ensure data accuracy and consistency through validation, cleansing, and governance frameworks.

Optimize data models, data lakes, and warehouses for identity analytics, access reviews, and compliance reporting. Develop and deploy solutions using Azure Data Factory, Databricks, SQL, and Spark, automating workflows and enhancing pipeline reliability.

Adhere to security standards, privacy regulations, and enterprise IAM policies. Collaborate with architects, security teams, and stakeholders to define data requirements and deliver high-quality enterprise identity data solutions. Comply with all company policies and directives.

A minimum of 7.5 years of dedicated experience in Data Engineering is required, with hands-on proficiency in cloud platforms like Azure Data Factory and Databricks. Expertise 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 is expected. Strong foundational skills in SQL, Python, PySpark, and ETL/ELT development are crucial for success in this role.