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Datavant logo
Datavant

Connecting the world’s health data to improve patient outcomes.

VP Data, ML Platforms

Vice PresidentVice PresidentFull TimeRemoteLeadTeam 201-500Since 2017H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

132 days ago

Salary

$250K - $300K / year

Seniority

Lead

Postgraduate Degree15 yrs expEnglish

Job Description

VP Data, ML Platforms

Datavant

• 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 • 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 • 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 • 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.

Job 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.

Benefits

  • Health insurance
  • 401(k) matching
  • Flexible work hours
  • Paid time off
  • Remote work options

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