VP Data Architecture & Integration
About The Position
The Vice President, Enterprise Data Architecture & Integration is responsible for the enterprise strategy, architecture, governance, and delivery of the organization's information assets. Reporting to the Chief Technology Officer, this senior leader role establishes the enterprise data architecture that enables operational excellence, financial transactions, external partner connectivity, regulatory compliance, analytics, and artificial intelligence. This role is accountable for ensuring enterprise data is modeled once, governed consistently, and delivered through secure, reliable, and scalable enterprise data services. The position leads enterprise data architecture, data governance, enterprise integration services, and enterprise data platform, including responsibility for EDI, client extracts, file-based integrations, APIs, and external partner connectivity. Working closely with Product, Engineering, Analytics, Operations, Finance, Commercial, and Compliance, this leader ensures enterprise information is treated as a strategic corporate asset supporting every major business capability.
Requirements
- Bachelor's degree in Computer Science, Information Systems, or related field; advanced degree preferred.
- 10 years leading enterprise data architecture, integration, or enterprise information management.
- 5 years in senior technology leadership.
- Healthcare payer experience strongly preferred.
- Demonstrated success leading enterprise architecture, governance, integration, and platform organizations.
- Familiarity with recognized architecture and governance frameworks such as TOGAF, DAMA-DMBOK or similar methodologies.
- Experience with cloud data and integration technologies, preferably within AWS.
Nice To Haves
- Cloud-native data platforms, data warehouses, data lakes, and operational data stores
- Healthcare interoperability including HIPAA X12, HL7, and FHIR
- API-first, event-driven, batch, and file-based integration architectures
- Master Data Management, metadata management, data catalogs, lineage, and governance
- AI-ready architecture including semantic models, vector-ready data, knowledge graphs, and retrieval architectures
- Security, privacy, HIPAA compliance, encryption, masking, and access controls
- Analytics engineering and transformation frameworks, pipeline orchestration, and data-quality testing and observability across the curated and consumption layers
Responsibilities
- Define and maintain the enterprise information architecture, canonical data model, and authoritative systems of record.
- Lead enterprise data governance, metadata, lineage, master data management, business glossary, stewardship, and data quality programs.
- Lead Enterprise Integration Services responsible for EDI, file-based interfaces, client extracts, regulatory submissions, APIs, trading partner onboarding, and third-party integrations.
- Define enterprise integration standards and reusable data exchange patterns to reduce point-to-point interfaces.
- Ensure data architecture supports operational systems (e.g. billing, claims processing, provider reimbursement, etc.), client reporting, analytics, and AI without unnecessary duplication.
- Partner with Analytics to deliver data through trusted metadata, semantic consistency, lineage, and governed data products.
- Provide executive oversight for availability, monitoring, SLA management, disaster recovery, and operational excellence of enterprise data services.
- Serve as the enterprise authority for information architecture and participate in architecture governance for major initiatives.
- Establish and maintain, jointly with Analytics, a shared semantic/metrics layer where core business definitions (e.g., member, enrollment, PMPM) are consumed consistently across operational reporting, client-facing analytics, and AI.
Benefits
- Improved enterprise data quality and reuse
- Reliable EDI, APIs, and external data exchanges
- Reduced duplicate data and integration complexity
- Faster onboarding of clients and trading partners
- Improved operational reporting and analytics enablement
- Enterprise data architecture that supports AI initiatives without significant redesign
- Core entity metrics (e.g., member and enrollment counts) are consistent and reconciled across operational, client, and analytics reporting from a shared
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What This Job Offers
Job Type
Full-time
Career Level
Executive
