Principal Architect, Payer Data Platform

Veradigm•Raleigh, NC

About The Position

Veradigm is building Health Network Architecture (HNA), a platform that brings its clinical, payer, and Life Sciences businesses onto shared foundations. The Principal Architect, Payer Data Platform defines and delivers the clinical and payer data foundation for Veradigm’s payer products on HNA, including how data is ingested, modeled through shared definitions and contracts, and accessed by products, analytics, AI features, and partners. The role also contributes to outcomes in risk adjustment, quality, care coordination, prior authorization, and CMS interoperability. This hands-on individual-contributor role establishes shared clinical and payer data definitions, contracts, and API and big-data access patterns. Product teams build on these foundations, while HNA platform architecture owns the overall platform design. The architect works alongside Product and engineering teams in the US and India and follows complex data problems through production. Approximately 25% of the role involves building reference implementations and shared primitives, with the remainder focused on design, design review, and delivery collaboration. The role designs data foundations that support accurate and safe AI features and uses AI in engineering work. It helps payer products give health plans a complete, current view of members and providers with faster access to information, reducing gaps that can contribute to delayed care, duplicated work, and decisions based on stale data.

Requirements

Bachelor’s degree or equivalent technical or business experience (required).
At least 5 years of experience designing data platforms for healthcare clinical and/or payer data, including claims, eligibility, or clinical records (required).
Expert knowledge of relational, dimensional, and FHIR resource modeling, canonical models, and data contracts.
Hands-on experience with healthcare data standards: X12 EDI, NCPDP, HL7 v2, C-CDA, FHIR R4, and major implementation guides; and code sets including ICD-10, CPT/HCPCS, LOINC, SNOMED CT, RxNorm, and NDC.
Experience with API and service design, including REST and FHIR APIs, event-driven design, and caching.
Ability to write and review production code in a major language such as Python, Java, or C#.
Working knowledge of payer business areas including risk adjustment, quality, care management, utilization management, prior authorization, and CMS interoperability rules.
Uses AI tools as part of daily design and engineering work.
Experience designing healthcare data for AI features, including grounding, structured extraction, evaluation, and PHI guardrails.
Understanding of how clinical data from provider systems flows into payer use cases such as risk adjustment and quality.
Ability to design internal platforms that other teams adopt, with clear contracts, sensible defaults, documentation, and migration paths.
Strength with cloud data platforms and ingestion, including AWS, cloud data warehouses or lakehouses such as Snowflake, relational databases, batch and streaming pipelines, and orchestration.
Knowledge of master data management and identity resolution for members and providers.
Knowledge of PHI security and compliance, including HIPAA, audit, and controls associated with HITRUST and SOC 2.
Knowledge of data quality, observability, and lineage practices.
Ability to explain data architecture clearly to engineers, product managers, and executives, in writing and in person.
Legally authorized to work in the United States or Canada; employment eligibility verification is required as a condition of hire.

Nice To Haves

Master’s degree (preferred).
10+ years of relevant work experience; 2–3 years at the Expert level or equivalent experience (preferred).
5+ years of practical experience designing and building enterprise or distributed software systems (preferred).
AWS Certified Solutions Architect – Professional or an equivalent cloud architecture certification (preferred).

Responsibilities

Design an ingestion framework for claims, remittance, enrollment, eligibility, pharmacy, lab, ADT, and clinical documents across X12, HL7, FHIR, and file feeds.
Establish end-to-end standards for data validation, reconciliation, provenance, observability, and safe reprocessing.
Define the architecture and sequence for moving existing payer feeds onto HNA without disrupting customers.
Design shared clinical and payer data definitions and contracts for payer products on HNA, enabling reuse while supporting distinct product workflows.
Govern data models, including versioning, schema evolution, extension approvals, and data contracts with producing and consuming teams.
Define appropriate access patterns for products and partners, including synchronous APIs, events, bulk exchange, analytical access, and FHIR-based interfaces where appropriate.
Design data access with Security and Privacy to meet HIPAA minimum-necessary, consent, and audit requirements within performance and cost targets.
Design data foundations for AI features, including definitions, provenance, and access controls that enable accurate and safe use of clinical and payer data.
Build reference implementations and shared primitives, and publish standards and examples that enable teams to adopt them independently.
Use AI in engineering work, including feed mapping, transformation generation and testing, and detection of data quality issues; establish patterns for teams to follow.
Review payer product data designs against shared standards and work with HNA platform architecture, which owns the overall platform design.
Work with Product from problem definition, translate product direction into data architecture, and stay engaged through delivery until product and platform outcomes are achieved.
Develop data-modeling skills across engineering teams.
Travel up to 20% as required.