VP Data & ML Platforms

Datavant is the data collaboration platform trusted for healthcare. Guided by our mission to make the world’s health data secure, accessible and actionable, we provide critical data solutions for organizations across the healthcare ecosystem - including providers, health plans, researchers, and life sciences companies. From fulfilling a single patient’s request for their medical records to powering the AI revolution in healthcare, Datavanters are building the future of how data is connected and used to improve health.

By joining Datavant today, you’re stepping onto a driven and highly collaborative team that is passionate about creating transformative change in healthcare.

The VP of Data & ML Platforms is a senior executive accountable for the strategy, architecture, and delivery of Datavant's enterprise data and ML platform.

This role owns the full data stack, from ingestion and storage through governance, compute, and AI/ML enablement, ensuring that Datavant's data assets are architecturally sound, well-governed, and positioned to scale through organic growth and acquisition.

This is not a governance-only position. The VP sets architectural direction, makes definitive technology decisions, and builds a high-performing engineering organization capable of operating at enterprise scale in a regulated healthcare environment. The role has authority over data platform architecture, governance standards, and AI infrastructure strategy, and is accountable for reliability, architecture maturity, governance adoption, and integration readiness

Key Responsibilities

Data Platform Architecture & Strategy

• Own the long-term enterprise data architecture, including the evolution of the company's data lake, cloud data warehouse, and clinical compute environments

• Drive and enforce a compute-agnostic platform strategy—where data lives in governed storage and multiple engines can query it without creating siloed copies

• Establish and mature dataset contracts, schema governance, and versioning standards that enable domain teams to evolve independently without breaking downstream consumers

• Make and communicate architecture decisions across catalog, ingestion, transformation, and compute

• Own data platform cost governance, ensuring infrastructure spend is transparent, attributable, and aligned with business value

Data Governance & Quality

• Establish formal data governance at enterprise scale, including ownership models, access controls, lineage, data quality standards, and compliance frameworks appropriate to healthcare (HIPAA, SOC 2, FedRAMP readiness)

• Own the metadata and governance layer, ensuring it is well-adopted across the organization, aligned with the broader catalog strategy, and portable rather than locked to a single vendor

• Drive data quality as an engineering discipline, embedding checks, monitoring, and accountability into platform and domain workflows.

• Ensure data access, permissioning, and change management processes are scalable and do not become bottlenecks to engineering velocity

AI & ML Infrastructure Enablement

• Own the AI/ML infrastructure layer, model training environments, compute provisioning (CPU/GPU), model deployment and serving frameworks, and MLOps tooling

• Ensure the data platform is AI-ready: well-cataloged, semantically rich, and accessible to data science and ML engineering teams across the organization

• Partner with business units and product teams to enable AI-driven workflows and analytics products by providing reliable, governed data foundations and scalable compute infrastructure

Team Leadership & Development

• Lead and develop the data engineering organization, spanning data platform infrastructure, clinical data engineering, data integration, ML platform, and data operations

• Assess organizational structure and talent against the demands of the platform at scale, making changes where necessary to ensure the right people are in the right roles

• Build a culture of architectural ownership, engineering rigor, and operational accountability

• Represent data platform and AI infrastructure strategy at the executive level, shaping investment priorities and contributing to enterprise technology strategy

• Partner with recruiting to attract and retain senior technical talent in a competitive market

Requirements

• 15+ years in technology leadership, with at least 5 years in a VP or senior director role leading enterprise data platform or data engineering organizations

• Proven track record building and scaling data platforms in complex, high-growth environments, ideally through periods of significant M&A activity

• Deep architectural expertise across the modern data stack: open table formats, cloud data warehouses, streaming infrastructure, transformation frameworks, and metadata/governance tooling

• Experience establishing data governance programs at enterprise scale, including ownership models, data quality frameworks, lineage, and access controls

• Strong understanding of AI/ML infrastructure, model training, serving, MLOps, and how data platform maturity enables AI adoption

• Experience leading in regulated or compliance-heavy environments (healthcare, life sciences, or financial services)

• Demonstrated ability to operate as a peer-level leader, credible with engineers, effective with executives, capable of making definitive architectural decisions under ambiguity

• Experience leading geographically distributed engineering teams

• Strong cost management instinct, able to balance platform investment against operational efficiency and budget constraints

We are committed to building a diverse team of Datavanters who are all responsible for stewarding a high-performance culture in which all Datavanters belong and thrive. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status.

At Datavant our total rewards strategy powers a high-growth, high-performance, health technology company that rewards our employees for transforming health care through creating industry-defining data logistics products and services.

The range posted is for a given job title, which can include multiple levels. Individual rates for the same job title may differ based on their level, responsibilities, skills, and experience for a specific job.

The estimated total cash compensation range for this role is:
$250,000—$300,000 USD

To ensure the safety of patients and staff, many of our clients require post-offer health screenings and proof and/or completion of various vaccinations such as the flu shot, Tdap, COVID-19, etc. Any requests to be exempted from these requirements will be reviewed by Datavant Human Resources and determined on a case-by-case basis. Depending on the state in which you will be working, exemptions may be available on the basis of disability, medical contraindications to the vaccine or any of its components, pregnancy or pregnancy-related medical conditions, and/or religion.

This job is not eligible for employment sponsorship.

Datavant is committed to a work environment free from job discrimination. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status. To learn more about our commitment, please review our EEO Commitment Statement here. Know Your Rights, explore the resources available through the EEOC for more information regarding your legal rights and protections. In addition, Datavant does not and will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay.

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