Senior Manager Data Engineering

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. As a Senior Manager of Data Engineering at Optum Rx, you will lead and mentor a high-performing team of data engineers in designing, building, and optimizing scalable, enterprise-grade data architecture and analytics platforms. In this role, you will champion AI adoption as a core driver of team success-integrating AI-enabled capabilities into data workflows, driving platform modernization across Azure, Snowflake, and Microsoft Fabric, and embedding responsible AI practices throughout the data lifecycle. You will partner with cross-functional leadership to transform complex pharmacy data into reliable, actionable insights that improve health outcomes and pharmacy benefit experiences for millions of people.

Integrate enterprise AI tools and AI-enabled capabilities into data engineering workflows, setting clear development goals and actively removing barriers to accelerate team adoption Champion the ethical and responsible use of AI across data platforms by embedding transparency, fairness, data privacy, and accountability throughout the entire data and AI lifecycle Strategically leverage AI and advanced analytics to solve complex health and pharmacy data challenges, unlock operational opportunities, and deliver tangible business value Champion AI as a core driver of team success, proactively shaping how AI-driven solutions are developed, deployed, and utilized across reporting and analytics domains Architect, design, and maintain scalable data pipelines, ETL/ELT workflows, and integration solutions across Azure and Snowflake environments Define data modeling standards (dimensional, relational, NoSQL) and optimize enterprise data platforms using Snowflake, Microsoft Fabric, and Azure data services Provide technical leadership and mentorship to data engineers, managing a team of 5+ resources while enforcing coding, testing, and CI/CD best practices Build and optimize batch and real-time streaming pipelines across APIs, databases, and streams using Kafka, Event Hubs, Airflow, Spark, and Databricks Implement data validation, lineage, governance frameworks, and metadata management (e.g., Azure Purview) while ensuring compliance with HIPAA, GDPR, and security standards Partner with business, BI, analytics, and data science teams to translate complex pharmacy requirements into performant, reusable technical designs 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 Required Qualifications: 10+ years of experience in Data Engineering or Data Science, including 3+ years in a technical leadership role managing a team of at least 5 resources 8+ years of hands-on experience in Data Engineering focused on ETL/ELT development using SQL, Databricks, Python, and Spark/PySpark 5+ years of experience in data modeling, query performance tuning, data streams, and secure data sharing 5+ years of