Principal Architect - Remote or Hybrid in MN and DC

Primary Responsibilities

• Define and drive the data architecture for Optum Health's Risk Adjustment and Quality platform
• Architect scalable, secure, and governed solutions that integrate claims, encounters, eligibility, provider, member, EHR, lab, pharmacy, and other clinical data into a unified data platform
• Design canonical, logical, and physical data models for core healthcare domains such as member/patient, provider, coverage, diagnosis, condition, encounter, procedure, medication, lab result, risk score, quality measure, and gap status
• Lead architecture for data products and pipelines that support:
• Risk Adjustment Framework
• Prospective and retrospective risk adjustment workflows
• Coding capture and suspecting
• HEDIS / Stars / NCQA reporting and gap closure
• Quality performance analytics and operational workflows
• Partner with business and domain leaders to ensure architecture supports the nuances of Medicare Advantage, quality programs, evolving CMS and NCQA requirements, and downstream operational use cases
• Ensure full alignment with HIPAA, PHI, privacy, security, access control, auditability, and data retention requirements
• Define and implement standards for data quality, lineage, metadata, semantic consistency, reconciliation, and traceability from source systems through measure/risk outputs
• Drive architecture decisions for identity resolution, provider and member mastering, source-of-truth alignment, and data harmonization across payer and provider ecosystems
• Collaborate with data engineering and platform teams on cloud-native architecture patterns including warehouse design, API-led integration, event-driven patterns, and high-volume batch/near-real-time processing
• Support audit-readiness for risk and quality programs, including traceability needed for RADV, NCQA validation/audits, and internal control frameworks
• Lead architecture reviews, create reusable standards and design patterns, and mentor senior engineers and architects across the organization
• Communicate complex technical concepts clearly to executive, operational, and clinical stakeholders

Required Qualifications

• Undergraduate degree in applicable area of expertise or equivalent experience
• 5+ years of experience in healthcare data architecture, data engineering, enterprise data, or information architecture, with increasing scope and seniority
• Demonstrated experience supporting HEDIS, Stars, and NCQA quality data needs, including quality measure data sourcing, attribution, gap identification, and reporting architecture
• Demonstrated expertise with healthcare interoperability standards including: FHIR, HL7, X12
• Demonstrated solid data modeling skills, including canonical models, dimensional models, and data product/domain-oriented design

Preferred Qualifications

• Master's degree in a relevant technical or healthcare field
• 2+ years in a lead or principal architecture role designing enterprise-scale healthcare data solutions
• Experience designing solutions on modern cloud data platforms and enterprise data ecosystems
• Experience establishing or enforcing data governance disciplines such as lineage, metadata, data quality controls, stewardship, and source-to-target traceability
• Experience in Medicare Advantage and other value-based care environments
• Experience with RAPS/EDPS, chart review data, coding operations, or provider documentation improvement workflows
• Experience supporting digital quality initiatives, eCQMs, CQL, or FHIR-based quality measurement
• Experience with provider clinical systems such as Epic, Cerner/Oracle Health, or other enterprise EHR platforms
• Experience with modern cloud technologies and tools such as Snowflake, Databricks, Azure, GCP, dbt, Kafka, or comparable platforms
• Experience with master data management, enterprise MPI/EMPI, or identity resolution frameworks
• Experience working in highly regulated, large-scale healthcare enterprises with complex partner ecosystems
• Solid knowledge of HIPAA/PHI requirements and secure data design principles including minimum necessary access, role-based controls, encryption, audit logging, and de-identification where appropriate
• Working familiarity with CCD/C-CDA and broader clinical exchange patterns
• Demonstrated expertise in healthcare data architecture across payer, provider, or integrated care settings
• Demonstrated domain expertise in CMS-HCC / RAF, including the data structures, workflows, and controls required to support risk adjustment use cases
• Exposure to AI/ML-enabled use cases such as risk suspecting, gap prioritization, or clinical NLP

Benefits

• Comprehensive benefits package
• Incentive and recognition programs
• Equity stock purchase
• 401k contribution (subject to eligibility)