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.

The Senior Manager - Data Engineering is a senior engineering and people leader accountable for building, scaling, and governing enterprise grade data engineering platforms that power AI/ML models, Forecasting, Finance, and Health Risk programs across Payment Integrity and Actuarial domains.

This role owns the data foundations, pipeline architecture, and platform reliability required to support model development, training, inference, and forecasting workloads, leveraging Azure Databricks, Snowflake, and GCP. The position partners closely with Data Science, AI/ML, Actuarial, Finance, and Product teams to ensure data engineering platforms are trusted, scalable, secure, and production ready.

Primary Responsibilities:

• Enterprise Data Engineering & Platform Architecture
  • Own and evolve enterprise data engineering architecture across Azure, Snowflake, and GCP
  • Design and standardize cloud native Lakehouse architectures optimized for AI/ML and forecasting workloads
  • Establish reference architectures, reusable frameworks, and engineering guardrails for ingestion, transformation, and consumption
  • Drive architectural decisions across performance, scalability, resilience, security, and cost optimization
• Advanced Data Engineering & Technology Leadership
  • Lead hands on technical guidance across:
    • Azure Databricks
    • Snowflake
    • GCP data services
    • Apache Spark (PySpark) , Python and SQL
  • Build and operate high volume, high reliability data pipelines supporting batch and near real time workloads
  • Ensure engineering excellence in:
    • Distributed processing and performance tuning
    • Data reliability, observability, and error handling
    • Schema evolution and backward compatibility
• AI/ML & Forecasting Data Enablement
  • Design and operate AI/ML ready data platforms supporting:
    • Feature engineering pipelines
    • Model training and inference data flows
    • Historical and point in time data management
  • Partner with Data Science and ML Engineering teams to:
    • Enable model friendly data structures
    • Support ML CI/CD and data versioning
    • Integrate data pipelines with ML lifecycle tools
  • Enable Forecasting and Finance programs with consistent, reproducible, and trusted data pipelines
• Payment Integrity & Actuarial Data Engineering
  • Build data engineering foundations supporting Payment Integrity programs, including:
    • Pre pay and post pay claim processing pipelines
    • Claims accuracy and leakage prevention workflows
  • Enable Actuarial and Health Risk programs by:
    • Supporting medical cost, utilization, and risk data pipelines
    • Ensuring alignment with claims lifecycle, pricing, benefits, and policy rules
  • Ensure solid data reconciliation and auditability for financially sensitive workloads
• CI/CD, Governance & Production Readiness
  • Own CI/CD pipelines for data and ML workloads, including:
    • Automated testing and validation
    • Environment promotion and release orchestration
  • Implement data quality, reconciliation, lineage, and monitoring frameworks
  • Ensure platforms meet HIPAA, regulatory, and enterprise security standards
  • Define and track KPIs for:
    • Pipeline reliability and freshness
    • Platform performance and cost efficiency
    • Production stability
• People Leadership & Engineering Culture
  • Lead and mentor senior managers, data engineering leads, and architects
  • Build a solid engineering first culture focused on quality, accountability, and ownership
  • Drive hiring, talent development, succession planning, and skills uplift for advanced data engineering roles
  • Act as a thought leader shaping enterprise data engineering strategy for AI at scale
• 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:

• 4-year graduation
• 15+ years of experience in data engineering, data platforms, or large scale data systems
• 4+ years in senior engineering leadership or people management roles
• Deep hands on expertise with:
  • Azure Databricks
  • Snowflake
  • GCP
  • Spark (PySpark) , Python and SQL
• Proven experience building CI/CD pipelines for data and AI/ML workloads
• Experience delivering enterprise scale, production data platforms
• Solid domain expertise in Payment Integrity, Healthcare Claims, Actuarial, Finance, or Health Risk systems
• Solid background working in regulated healthcare environments

Preferred Qualifications:

• Experience supporting ML platforms, forecasting engines, or risk models
• Experience leading global, distributed engineering teams
• Familiarity with medical economics, utilization, affordability, and risk adjustment
• Exposure to data governance, metadata management, and platform observability

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.