Head of Data & Analytics

Vanta · Enterprise · U.S. · Remote · Product Analytics

Head of Data & Analytics to lead a team responsible for Vanta's analytics and data platform, owning the architecture, ingestion, modeling, and governance. The role will deliver key business insights and create AI-first self-serve experiences, leveraging AI to drive efficiency and impact. Requires strong subject matter expertise in SaaS and a technical architecture mindset.

What you'd actually do

  1. Define and execute Vanta’s company-wide data infrastructure strategy — setting the vision for how data is collected, governed, and used to drive outcomes.
  2. Partner with executives and functional leaders across Product, Marketing, Revenue, and Finance to align data priorities with business goals.
  3. Foster a culture of data-driven decision-making across Vanta through effective storytelling and clear communication
  4. Create AI-first self-serve experiences so it’s easy for every Vanta’n to get the data they need
  5. Lead and grow a team of data scientists and analysts that: Delivers actionable insights Develops an analytics roadmap that connects operational metrics with strategic goals, driving efficiency, growth, and customer impact. Drives consistency and rigor in how we measure product success — ensuring shared definitions, trusted data, and transparency
  6. Lead and grow a data engineering team that: Develops, operates, and maintains Vanta’s internal analytics infrastructure, including Snowflake, DBT and Dagster - architecting and re-architecting these systems to enable efficient operations at scale as well as high availability, ease of use, and strong governance and security Enables analysts, data scientists, and partner organizations to quickly and efficiently build analyses and answer critical business questions across all departments Builds and maintains strong data pipelines that ensure data from our business systems and product efficiently and cleanly enters our data infrastructure.

Skills

Required

  • 15+ years of experience in data engineering and analytics
  • track record of leading high performing teams
  • subject matter expertise in SaaS
  • deep understanding of modern data stacks (Snowflake, dbt, Airflow, etc.)
  • data modeling
  • integration frameworks
  • translating complex data into clear, actionable insights
  • engineering and automation-driven approach to systems architecture
  • experience using systems automation and AI to drive efficiency
  • establishing unified data definitions, governance processes, and mappings
  • Open to using AI to amplify their skills and strengthen their work

What the JD emphasized

  • AI-powered data infrastructure
  • AI-first self-serve experiences
  • using systems automation and AI to drive efficiency