Data Architect - Minneapolis, MN

UnitedHealth Group•Minnetonka, MN

1d•Hybrid

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 Enterprise Data Architect will lead the end to end architecture design of scalable, governed, and interoperable data ecosystems across the Healthcare enterprise. This role enables advanced analytics, Payment Integrity (PI), actuarial forecasting, AI/ML workloads, and enterprise reporting by designing data models, pipelines, governance frameworks, and Lakehouse patterns that support high quality, secure access to claims, provider, member, and operational datasets. The architect acts as a strategic partner to business, technology, and analytics teams-ensuring unified data standards, robust lineage, architectural compliance, and alignment to enterprise data strategy.

Requirements

15+ years of Data Engineering
8+ years of experience architecting large-scale data systems in healthcare or regulated industries
8+ years of experience with Databricks Lakehouse (Delta Lake, Unity Catalog, DLT, Workflows)
5+ years of hands on expertise with Azure (ADF, Data Lake Storage, Event Hub, Azure SQL, Key Vault) or equivalent cloud
5+ years of data modeling (OLTP, OLAP, canonical, semantic models)
4+ years of experience with healthcare data domains, especially claims adjudication, pricing, provider data, and membership data
Understanding MDM, metadata management, and enterprise data governance frameworks
Reside in Minneapolis, MN and have the ability to commute to the office per Optum’s hybrid policy

Nice To Haves

Bachelor’s degree required; Master’s
Experience working with EHR/clinical datasets (HL7/FHIR, CCD, claims-evidence alignment)
Experience enabling AI/ML platforms, including feature store design, MLflow setup, and model deployment architecture
Experience with enterprise semantic models for BI platforms (Power BI, Tableau)
Familiarity with actuarial datasets, forecasting processes, and PI analytics domains
Databricks Lakehouse, Cloud Native Data Architecture (Azure preferred)
Understanding of Provider RCM workflows (billing, coding, authorizations)
Proven exposure to Call Center datasets (member & provider telephony data)

Responsibilities

Define and drive enterprise data strategy while guiding multiple engineering and analytics teams
Function as SME in healthcare data landscapes and Lakehouse architectures
Influencing enterprise decisions and architecting platforms that support PI, actuarial, AI/ML, and operational needs
Working collaboratively with Data Science and AI Teams to lead successful delivery
Supporting cross-functional leadership and long-term architectural vision
Define the enterprise data architecture roadmap, covering ingestion, curation, consumption, master data, metadata, and governance layers
Establish Lakehouse architectural patterns (Bronze/Silver/Gold), Delta Lake standards, and reusable semantic models in Databricks
Drive modernization of legacy data systems into cloud-native, scalable Databricks based platforms
Partner with enterprise architects to align data architecture with cloud, security, integration, and platform strategies
Create enterprise wide healthcare data models covering Claims, Provider, Member, Eligibility, Pricing, and Utilization domains
Develop canonical data models, dimensional schemas, and semantic layers to support PI, actuarial, clinical, and operational analytics
Guide end to end lineage, metadata management, and data cataloging using Unity Catalog, Purview, or similar tools
Architect data flows for structured and semi structured datasets (EHR, RCM, call center interactions)
Provide architectural oversight for Databricks pipelines, including ingestion, transformations, DLT, workflows, and feature pipelines
Ensure architectural principles for reliability, performance, and cost efficiency are embedded in engineering workflows
Mentor engineering teams on Spark optimization, Delta Lake performance tuning, and scalable design practices
Evaluate new tools, frameworks, and architectural enhancements to improve throughput and reliability
Lead PHI-compliant data design, access controls, and governance frameworks aligned with HIPAA and enterprise policies
Define policies for RBAC, lineage, data quality SLAs, schema evolution, and data lifecycle management
Partner with Security, Compliance, Legal, and Audit teams to ensure enterprise-grade data operations
Work closely with PI leaders, actuarial teams, product owners, and analytics partners to translate business goals into scalable data architecture
Facilitate design reviews, architectural sign-offs, and stakeholder alignment sessions
Create reference architectures, playbooks, and reusable frameworks for cross-functional teams