Senior Manager Data Engineering
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. The Reporting Analytics and Data (RAD) team is seeking a Senior Manager of Data Engineering to help design, build, and support modern data solutions across UnitedHealth Group’s Enterprise Services organization. In this role, you will lead the development of scalable ETL pipelines, data repositories, and integration patterns that bring together information from multiple enterprise systems and make it available for analytics, reporting, automation, AI/ML-enabled solutions, and business decision-making. You will partner closely with business and technology stakeholders to understand data needs, translate requirements into durable engineering solutions, and ensure data is reliable, accessible, and structured for long-term use. This role is ideal for someone who enjoys hands-on data engineering while also providing technical guidance, promoting best practices, and helping mature the team’s data platform capabilities. You will enjoy the flexibility to telecommute from anywhere within the U.S. as you take on some tough challenges.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Analytics, or a related field
- 5+ years of experience in data engineering, analytics, or data platform development
- 5+ years of experience with SQL/Snowflake, Python, data modeling, ETL/ELT development, data integration, performance optimization, and data pipeline orchestration
- 3+ years of demonstrated experience designing, building, and managing large-scale cloud-based data platforms using technologies such as Snowflake, Azure Data Factory (ADF), Azure Data Lake, Databricks, and enterprise data warehousing solutions
- 3+ years of experience implementing modern software development practices, including source control and CI/CD using GitHub, automated testing, code reviews, release management, and infrastructure-as-code methodologies within data engineering environments
- 3+ years of experience in a people leadership or management role
Nice To Haves
- Advanced degree
- Experience supporting analytics, reporting, and AI/ML workloads, including the data pipelines, feature engineering, model-ready datasets, and operational practices needed to move solutions from development into production
- Familiarity with modern AI/ML solution patterns and technologies such as vector databases, retrieval-augmented generation (RAG), large language models (LLMs), agentic frameworks, MLOps, and common Python ML libraries
- Proven ability to lead high-performing technical teams, drive strategic initiatives, manage competing priorities, and partner effectively with business, analytics, architecture, and technology stakeholders to deliver scalable data solutions and measurable business outcomes
Responsibilities
- Define and execute the data engineering roadmap, aligning platform, architecture, and data delivery priorities with business objectives while ensuring measurable outcomes and long-term scalability
- Lead, mentor, and develop a team of data engineers and technical leads, fostering a culture of accountability, innovation, continuous improvement, and professional growth
- Direct the design, development, and support of scalable data pipelines, ETL/ELT processes, cloud-based data platforms, and data warehousing solutions to deliver trusted, high-quality data for analytics and operational reporting
- Establish and enforce data governance standards, data quality controls, platform reliability practices, and operational processes to ensure secure, compliant, and dependable data assets across the organization
- Collaborate with business stakeholders, analytics teams, architects, and product leaders to prioritize initiatives, resolve cross-functional dependencies, and translate business requirements into scalable data and analytics solutions
- Partner with data science and AI/ML teams to establish reusable, governed data foundations that support model development, retrieval-augmented generation, intelligent automation, and production AI/ML workloads
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
