Data Architect

Advisor, Data Architect

We are looking for a senior data architect to lead the data architecture practice across a large, multi-product government healthcare technology platform. This is a hands-on advisory role — you will define how data is modeled, owned, integrated, and governed across a portfolio of products that collectively process millions of healthcare claims, enrollments, provider interactions, and financial transactions annually. You will work with product teams, engineers, and enterprise architects to establish canonical data models, draw and defend domain boundaries, and set the standards that keep a complex distributed system coherent as it modernizes.

What You Will Do

Data Modeling and Canonical Design

Define and govern enterprise-wide canonical data structures — the authoritative record definitions for key entities such as claims, members, providers, benefits, and financial settlements. Apply a layered data modeling approach: conceptual, logical, implementation, and analytics consumption. Ensure entity definitions remain consistent and non-duplicated across independently evolving product domains. Set and enforce naming conventions, data classification standards, and normalization rules.

Domain Architecture and Bounded Context Design

Map the data domains across the product portfolio, define ownership boundaries, and document what each domain owns vs. consumes. Apply Domain-Driven Design principles: bounded contexts, ubiquitous language, domain events, and anti-corruption layers at integration seams. Define integration contracts between domains with clear ownership and versioning expectations. Guide legacy platform coexistence strategies during modernization.

Claims and Transaction Data Architecture

Own the data architecture for high-volume transaction processing pipelines — claim intake, adjudication, financial accumulation, and settlement. Design reference data management patterns: versioned snapshots that support point-in-time replay and audit. Define deduplication and cross-system indexing strategies across claims, adjustments, voids, and resubmissions.

Schema Governance and Event Design

Own the enterprise schema registry — govern all event schemas across distributed services, enforce versioning discipline, and maintain lineage back to the canonical model. Enforce backward-compatible schema evolution: additive-only consumer contracts, deprecation windows, and compatibility enforcement. Review and approve schema changes before production promotion.

Compliance and Regulatory Data Architecture

Define data architecture for regulatory reporting pipelines and government data submissions. Own data classification across all canonical structures — field-level tagging, lineage from collection through disposition. Design canonical mapping layers for interoperability standards required by regulation.

Architecture Governance

Author and maintain data architecture patterns and standards used across engineering teams. Review technology proposals and vendor submissions for data architecture compliance. Establish and enforce the data ownership boundary rule: one owning domain per canonical entity.

What You Bring

Core Skills

10+ years of data architecture experience in complex, multi-product or multi-domain environments. Deep expertise in enterprise data modeling across conceptual, logical, and physical layers. Strong command of Domain-Driven Design: bounded contexts, aggregates, domain events, anti-corruption layers. Experience designing and governing event-driven architectures and schema registries. Hands-on with cloud data platforms — AWS or Azure. Proficiency in SQL and Python for data engineering, pipeline logic, and validation. Experience with medallion or lakehouse architecture (Bronze, Silver, Gold).

Collaboration and Communication

Ability to translate complex data architecture decisions into clear guidance for engineering teams. Comfortable presenting trade-offs to senior technical leadership. Experience authoring architecture standards and patterns consumed by multiple teams.

Preferred

Experience with government healthcare programs such as Medicaid, CHIP, or Medicare. Familiarity with healthcare data standards: X12 EDI, NCPDP, FHIR R4, or HL7. Background in claims processing systems or health plan administration is a strong advantage but not required.