The Role
Leads enterprise Data and AI platform strategy, data engineering, AI/ML operationalization, governance, modernization, and cloud cost optimization. Oversees data products, pipelines, APIs, real-time processing, MLOps, GenAI, Agentic AI, vector databases, RAG, monitoring, and Responsible AI. Partners with executives and technical stakeholders to prioritize platform investments, establish performance metrics, manage budgets and vendors, and build high-performing engineering teams.
Summary Generated by Built In
Requisition Number: 2392368
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.
Primary Responsibilities:
Required Qualifications:
Success Metrics
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
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.
Primary Responsibilities:
- Define and lead the enterprise Data & AI Platform Strategy, ensuring scalable, secure, resilient, and cost-efficient platforms for Analytics, ML, GenAI, and Agentic AI
- Build AI-ready data foundations using semantic layers, metadata management, data lineage, knowledge graphs, and governance frameworks
- Lead data engineering teams responsible for ingestion, transformation, storage, pipelines, APIs, data products, and real-time data solutions
- Establish engineering standards, reusable frameworks, and drive modernization of legacy systems into cloud-native architectures
- Partner with Data Science and AI teams to operationalize ML, GenAI, and Agentic AI solutions
- Enable capabilities such as feature stores, vector databases, embeddings, RAG, model deployment, monitoring, observability, explainability, and Responsible AI
- Drive enterprise-wide data governance, including data quality, stewardship, cataloging, lineage, master data management, privacy, and compliance
- Govern both AI training datasets and AI-generated outputs
- Promote a Data-as-a-Product operating model with defined ownership, SLAs, and quality standards
- Prioritize platform and data initiatives based on business value, AI readiness, and measurable outcomes
- Evaluate and implement emerging technologies including GenAI, Agentic AI, Data Fabric, Semantic Layers, Knowledge Graphs, and Intelligent Automation
- Lead proofs of concept and scale successful innovations across the enterprise
- Partner with business, product, analytics, and technology leaders to align platform investments with strategic objectives
- Present technology strategy and roadmap recommendations to executive leadership
- Manage budgets, vendors, cloud spend, operational performance, and platform reliability
- Establish KPIs for performance, availability, productivity, automation, and cost optimization
- Build, mentor, and develop high-performing Data & AI engineering teams
- Foster innovation, accountability, continuous learning, talent development, and career growth
- Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements
Required Qualifications:
- Extensive leadership experience in Data Engineering, Data Platforms, AI/ML Platforms, or Enterprise Data Architecture
- Experience implementing Data-as-a-Product frameworks and enterprise data strategies
- Experience managing large-scale engineering organizations, budgets, vendors, and cloud cost optimization initiatives
- Solid expertise in cloud-based data ecosystems and modern data platform architectures
- Deep knowledge of data engineering concepts including data pipelines, APIs, data products, streaming, and real-time processing
- Hands-on understanding of AI/ML operationalization, including:
- MLOps
- GenAI
- Agentic AI
- Vector Databases
- RAG (Retrieval-Augmented Generation)
- Embeddings
- Model Deployment & Monitoring
- Responsible AI
- Solid understanding of enterprise data governance, data quality, lineage, metadata management, cataloging, MDM, privacy, and regulatory compliance
- Knowledge of emerging technologies such as:
- GenAI
- Agentic AI
- Data Fabric
- Knowledge Graphs
- Semantic Layers
- Intelligent Automation
- Solid stakeholder management and executive communication skills
- Proven ability to build and lead high-performing teams across data engineering, analytics, governance, and AI domains
- Demonstrated success in driving platform modernization, digital transformation, and enterprise-scale technology adoption
Success Metrics
- Data quality and reliability
- AI adoption and business impact
- Platform availability and performance
- Data product adoption
- Engineering productivity and automation
- Cloud cost optimization
- Regulatory compliance
- Team engagement and retention
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
Skills Required
- Extensive leadership experience in data engineering, data platforms, AI/ML platforms, or enterprise data architecture
- Experience implementing Data-as-a-Product frameworks and enterprise data strategies
- Experience managing large-scale engineering organizations, budgets, vendors, and cloud cost optimization initiatives
- Expertise in cloud-based data ecosystems and modern data platform architectures
- Knowledge of data pipelines, APIs, data products, streaming, and real-time processing
- Understanding of MLOps, GenAI, Agentic AI, vector databases, RAG, embeddings, model deployment and monitoring, and Responsible AI
- Understanding of enterprise data governance, data quality, lineage, metadata management, cataloging, MDM, privacy, and regulatory compliance
- Knowledge of GenAI, Agentic AI, Data Fabric, knowledge graphs, semantic layers, and intelligent automation
- Strong stakeholder management and executive communication skills
- Ability to build and lead high-performing teams across data engineering, analytics, governance, and AI
- Demonstrated success driving platform modernization, digital transformation, and enterprise-scale technology adoption
Optum Compensation & Benefits Highlights
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Leave & Time Off Breadth — PTO is generally described as decent or good, and many note it as a strong part of the package. Actual ability to take time off can depend on workload and team coverage.
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Retirement Support — Offerings include a 401(k) with employer match and access to an employee stock purchase plan, which are highlighted as meaningful components of total rewards. These programs are consistently referenced among core benefits.
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Parental & Family Support — Parental and caregiver leave, along with adoption assistance, are publicly highlighted and viewed as notable elements of the package. Availability can be role-specific, but these supports contribute to overall breadth where offered.
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The Company
What We Do
Optum, part of the UnitedHealth Group family of businesses, 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. At Optum, we support your well-being with an understanding team, extensive benefits and rewarding opportunities. By joining us, you’ll have the resources to drive system transformation while we help you take care of your future. We recognize the power of connection to drive change, improve efficiency and make a difference in health care. Join a team where your skills and ideas can make an impact and where collaboration is key to creating technology that produces healthier outcomes.
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Optum Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Optum has three workplace models that balance the needs of the business and the responsibilities of each role. These models, core on‑site (5 days/week), hybrid (4 days/week) and telecommute or fully remote, vary by country, role and location.
Typical time on-site:
Not Specified
