Director of Architecture and Data Strategy - Remote

UnitedHealth Group•Minnetonka, MN

7d•$134,600 - $230,800•Remote

About The Position

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care’s most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. Reporting to the LOB Chief Architect & AI Officer, you will own the data strategy and target-state data architecture for the Community & State (C&S) line of business - setting direction for how C&S data is modeled, governed, and served, and steering the engineering teams that execute it. You will collaborate with and contribute to UHC- and UHG-level data strategies and workstreams, ensuring C&S both aligns with and helps shape enterprise direction. You'll stay close enough to the craft to validate key assumptions yourself, while driving delivery through the teams around you rather than through personal execution. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Requirements

10+ years of experience in data architecture, data engineering, data analytics, information management, or closely related technical disciplines
5+ years defining, evaluating, and validating enterprise-scale or large-domain data architecture strategies through proofs of concept, pilots, architecture reviews, and production adoption
4+ years with modern cloud data platforms and distributed data architectures, including Snowflake, Databricks, BigQuery, Azure Synapse, or equivalent, as well as lakehouse and streaming architectures
3+ years in senior architecture, domain architecture, or technical leadership roles setting technology strategy and influencing architectural direction
3+ years of hands-on experience designing and validating data models across multiple paradigms, including dimensional modeling, Data Vault, semantic layers, knowledge graphs, and vector/embedding representations
2+ years designing or piloting Generative AI and LLM-powered solutions, with working knowledge of RAG, grounding strategies, evaluation frameworks, vector search, and agentic patterns sufficient to steer and challenge engineering teams
Hands-on experience with enterprise metadata, data governance, data catalog, lineage, semantic, and AI-ready data platform capabilities
Experience working in highly regulated environments with solid security, privacy, compliance, and risk management requirements
Proven experience establishing data architecture standards, reference architectures, data contracts, and governance models across large, distributed engineering organizations
Working proficiency in Python and SQL sufficient to review technical work, reason about trade-offs, and challenge engineering teams - independent prototype-building not required
Demonstrated ability to drive architectural transformation and technology adoption through technical leadership, senior-leader and engineering-leader communication, influence, and validated proof points rather than direct organizational authority

Nice To Haves

Master's degree or advanced training in Computer Science, Data Science, or a related discipline
Bachelor's degree in Computer Science, Engineering, Data Science, or a related field (or equivalent professional experience)
Experience with health care data, Medicaid, or government-sponsored programs relevant to Community & State
Experience leading a data architecture function at a high-growth product company or AI-native organization
Background in machine learning engineering, applied AI research, or production ML systems
Published technical writing, conference speaking engagements, or open-source software contributions in data architecture or AI

Responsibilities

Own the target-state data architecture for the Community & State line of business, with a clear path from current to future state, and contribute to UHC- and UHG-level data strategy and workstreams
Serve as the translation layer between business and technology - interpret business use cases and problems-to-be-solved and determine what they mean for data: how it must be sourced, modeled, governed, and served
Translate technology and data strategy into business terms, driving alignment across C&S leaders and stakeholders on the rationale behind architectural direction, trade-offs, and investment
Direct and review the pilots and proof-of-concept work that validate architectural recommendations - guiding engineering teams and validating key assumptions yourself before the organization adopts them
Design semantic and metadata layers, ontologies, and knowledge systems that let humans and AI agents reason over the same data, working with engineering teams to prove them out
Evaluate emerging AI research, technologies, and architecture trends - including RAG, agentic patterns, and vector/embedding systems - to inform solution design and strategic investment decisions
Author reference architectures, design patterns, and data contracts that C&S engineering teams adopt and build against
Establish data governance, data quality, privacy, security, and AI-safety frameworks that protect business assets while accelerating delivery for the teams building on top of them
Drive architectural alignment across the C&S engineering teams through technical influence, documentation, and validated proof points rather than delivery authority
Partner with engineering, security, legal, compliance, and infrastructure leaders to inform build/buy/retire decisions and shape data platform investments for C&S
Model responsible, efficient AI adoption and set the expectation for how C&S teams use enterprise-approved AI tools and automation platforms