Senior Tech Product Manager

UnitedHealth Group•Eden Prairie, MN

15h•$91,700 - $163,700•Remote

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, and data they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits, and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together. As a Senior Technical Product Manager, you will drive the vision, technical product strategy, and engineering roadmap for an enterprise curated claims data layer spanning over 2,000 tables. In this role, you will design, develop, and deploy AI-ready data solutions that power downstream conversational analytics, generative AI tools, and enterprise decision-making platforms. You will lead cross-functional engineering teams to transform raw healthcare claims data into highly structured, compliant, and performant data products, while leveraging modern AI tools and data engineering frameworks to streamline workflows and drive continuous product innovation. You will enjoy the flexibility to telecommute from anywhere within the U.S. as you take on some tough challenges.

Requirements

Bachelor’s degree OR 4+ years of equivalent software engineering/data product management experience In Lieu of degree
5+ years of experience in technical product management, data product management, or data engineering leadership roles
5+ years of experience in Data Governance (e.g.: data utilization, risk assessment tools)
3+ years of hands-on experience working with large-scale healthcare data assets, specifically healthcare claims datasets spanning enterprise data warehouses or data lakes or experience in semantic Modeling and management
2+ years of experience defining technical product requirements, data models, and pipeline specifications for analytics or AI/ML workloads
2+ years of experience building, deploying, or managing AI-powered tools, conversational analytics infrastructure, or machine learning data pipelines
2+ years of experience with cloud data platforms (e.g., Snowflake, Databricks, Azure) and advanced SQL data querying tools

Nice To Haves

Demonstrated experience managing complex data assets containing thousands of tables/schemas in enterprise healthcare or technology environments
Deep domain knowledge of medical claims, pharmacy claims, EDI 837/835 transactions, and healthcare coding taxonomies (ICD-10, CPT, CPG)
Knowledge of Generative AI architectures, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and vector databases
Hands-on experience utilizing AI development tools to automate data validation, code generation, or product workflow tracking
Experience in Agile/Scrum delivery environments utilizing tools such as Jira and Confluence

Responsibilities

Define and execute the end-to-end technical product strategy and roadmap for a curated claims data layer comprising 2,000+ tables
Design, develop, and deploy AI-powered data solutions and layer architectures to address complex business challenges with an emphasis on responsible and ethical use of AI
Leverage enterprise-approved AI tools to streamline workflows, automate data pipeline tasks, and drive continuous product delivery improvements
Evaluate emerging trends in AI, machine learning, and cloud data architecture to inform solution design, data modeling, and strategic innovation
Partner with data engineering, cloud architecture, and AI platform teams to establish high-performance data pipelines, schemas, lineage, and access controls optimized for conversational analytics
Translate business use cases and conversational AI requirements into detailed product specifications, data dictionaries, schema definitions, and prioritized feature backlogs
Establish data quality, governance, and security standards across all claims data assets to ensure compliance and high accuracy for downstream analytical consumption
Monitor product usage, pipeline performance, and latency metrics to continuously refine data availability and self-service analytics patterns
Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI