Vice President, Data & Insights

GitLab

8h•Remote

About The Position

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.

Requirements

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

Responsibilities

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.