Data Platform Architect

Job Description

Our client is an innovative healthcare technology organization focused on transforming care delivery through the integration of clinical expertise, advanced analytics, digital engagement tools, and value-based operating models. The organization is evolving its next-generation operating framework, leveraging real-time patient intelligence, predictive analytics, and AI-driven decision-making to optimize outcomes, operational efficiency, and resource allocation.

To support this evolution, the organization is investing in a modern data and AI ecosystem capable of ingesting, processing, scoring, and acting on complex healthcare data in near real time. This platform will serve as a foundational capability for future growth, expansion into additional care domains, and the continued development of proprietary analytics and decision-support systems.

The Data Platform Architect will lead the strategy, design, and execution of this platform, partnering closely with data, engineering, product, clinical, and operational stakeholders. This is a hybrid strategy-and-architecture role reporting to data leadership, requiring the ability to navigate executive conversations while remaining deeply involved in technical architecture and platform design.

Primary Responsibilities:

Define Data Strategy

-Own and evolve the organization's long-term data strategy, supporting operational optimization, advanced analytics, AI initiatives, and future business expansion.

-Guide executive stakeholders through architecture, investment, and technology tradeoffs.

-Help establish and protect strategic data assets, including patient and provider intelligence models, proprietary outcome frameworks, and decision-support capabilities.

Architect the Data Platform

-Design and oversee the end-to-end healthcare data architecture, including data ingestion, event-driven integrations, identity resolution, lakehouse environments, feature stores, decisioning systems, orchestration layers, and observability capabilities.

-Establish enterprise standards for data architecture, including event taxonomy, schema management, metadata governance, and data contracts.

-Ensure scalability, flexibility, and interoperability across a rapidly evolving data ecosystem.

Lead Vendor and Technology Strategy

-Evaluate, select, and manage strategic technology partners across healthcare data, claims processing, provider intelligence, AI, customer data platforms, and analytics solutions.

-Drive architecture decisions that promote portability, interoperability, and vendor independence.

-Partner with legal, security, and compliance teams on data-sharing agreements, governance standards, and business associate agreements.

Establish Data Governance and AI Controls

-Create and enforce standards for HIPAA compliance, PHI protection, data governance, and responsible AI practices.

Implement controls for data classification, access management, data lineage, auditability, consent management, and training-data governance.

-Ensure all AI and analytics initiatives meet enterprise security, compliance, and explainability requirements.

Partner Across the Organization

-Translate architectural vision into actionable roadmaps and delivery plans for engineering teams.

-Collaborate with clinical stakeholders to support quality measurement, outcomes tracking, and analytics initiatives.

-Partner with operations and product teams to improve data capture, workflow efficiency, and decision-making processes.

-Align technology investments with business objectives and operational priorities.

Additional Responsibilities

-Perform other duties and strategic initiatives as assigned.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

-10+ years working with healthcare data, including 4+ years in architecture or strategy leadership

-Deep hands-on knowledge of healthcare data: X12 EDI (270/271/276/277/278/834/835/837), FHIR R4, HL7 v2 (especially ADT), CCD/C-CDA, NCPDP, and the realities of integrating with payers, EHRs, clearinghouses, and HIEs

-Experience working with AI team developing predictive models and ability to act as the liaison between AI modeling and data platform.

-Proven track record designing production data platforms at scale, streaming and batch, with managed Kafka or equivalent, lakehouse architectures (Snowflake / Databricks / BigQuery), dbt-style orchestration, modern observability

-Solid grounding in ML/AI systems: feature stores, point-in-time correctness, model lifecycle, NLP for clinical text. You evaluate model proposals on their merits

-Direct experience with patient identity resolution (deterministic + probabilistic) and tokenization (Datavant or equivalent)

-Working knowledge of value-based care economics: MLR, attribution, episode costing, risk adjustment, and how reimbursement models shape data requirements

-Demonstrated executive presence: framing tradeoffs, defending recommendations, adjusting when wrong, staying technically credible

-HIPAA-fluent. You engineer PHI minimization, BAA structures, and audit requirements as first-class concerns

-Ability and willingness to travel up to 10% as needed for onsite meetings, team collaboration, and company events. -Hands-on experience with at least one major longitudinal claims dataset (Komodo, Truveta, HealthVerity, Optum, IQVIA) and integration

-Highly collaborative and experienced with a broad range of business holders

-Experience integrating clinical data networks

-Experience with conversational AI in a contact-center context (Cresta, Observe.AI, or built in-house)

-Multi-payer scale experience

-Early-stage / scaling startup background, comfort with ambiguity and the ability to make calls without perfect information