An Overview of This Role

GitLab is seeking a VP of Data and Insights to lead the strategic vision, architecture, and execution of our enterprise data platform and analytics capabilities. Reporting to the CIO, you'll oversee a distributed team spanning data platform and engineering, analytics engineering, data governance, and data analysts embedded across business functions. This role represents a transformational opportunity to move GitLab beyond traditional dashboard development toward a truly AI-enabled, self-service data organization where stakeholders access insights on demand and data analysts focus on high-value strategic work. You'll be a trusted advisor to the executive team and a key driver of GitLab's AI journey, building the certified data foundations that power intelligent, consumption-aware decisions across the business.

What You'll Do

• Data Platform Strategy and Roadmap - Define and execute a multi-year strategy for GitLab's data platform, prioritizing certified datasets, clean schema architecture, and the infrastructure needed to support AI-native consumption and self-service access across the enterprise.
• AI-Enabled Self-Service Analytics - Lead the transformation from analyst-dependent reporting toward AI-powered self-service models, enabling business stakeholders to perform analysis and access insights independently while freeing the data team to focus on deeper strategic work.
• Data Platform Engineering Leadership - Oversee the architecture and evolution of GitLab's data engineering foundations, ensuring the team moves beyond reactive pipeline work toward scalable, AI-ready infrastructure that business functions can confidently build on.
• Analytics Engineering and Semantic Layer - Drive analytics engineering practices that produce governed, well-documented, and reusable data models. Champion the shift from ad hoc dashboard production to curated data products that serve as a single source of truth.
• Consumption and Usage-Based Data Strategy - Build deep expertise in GitLab's consumption and usage-based business model, ensuring the data organization can surface the metrics, trends, and signals that matter most to Revenue, Finance, and Product stakeholders.
• Data Governance and Quality - Establish and maintain enterprise-wide data governance frameworks, including data quality standards, access policies, lineage documentation, and accountability structures that instill trust in GitLab's data assets.
• Executive and Cross-Functional Partnership - Serve as a strategic thought partner to leaders across Sales, Finance, Product, and People, translating complex data questions into scalable answers. Build strong relationships across the e-group while ensuring the data team earns appropriate recognition for its contributions.
• Team Leadership and Development - Inspire and develop a high-performing distributed team across data platform, analytics engineering, governance, and analyst functions. Foster async-first culture, set clear expectations, and build a team that is proactive, strategic, and deeply engaged with the business.
• AI and Emerging Technology Adoption - Stay ahead of the curve on evolving data tooling, AI agents, and vibe-coded or curated analytics applications. Identify where emerging approaches can accelerate GitLab's data maturity and bring a point of view on what the future of data consumption looks like at scale.

What You'll Bring

• 12+ years of progressive data leadership experience, with 5+ years managing multi-functional data teams at high-growth SaaS companies
• Deep expertise in modern data platform architecture, including experience with database schemas, certified datasets, and the tooling and practices that enable AI-ready data infrastructure
• Proven track record driving self-service analytics transformation, moving organizations away from analyst bottlenecks toward scalable, AI-enabled data consumption models
• Strong understanding of consumption and usage-based business models and the data complexity they introduce, including usage tracking, metered billing, and the metrics that drive recurring revenue businesses
• Experience leading analytics engineering functions, including dbt, semantic layers, or similar approaches to building governed, reusable data models at scale
• Demonstrated ability to partner with and influence C-level and VP-level stakeholders across Sales, Finance, Product, and People functions, with strong executive presence and business acumen
• Track record of developing and retaining high-performing distributed teams in fully remote, async-first environments
• Strategic thinker with an unconventional point of view on where data and AI are heading, and the technical depth to distinguish signal from noise when evaluating new approaches