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Overview
Lead / Manager

Vice President, Data & Insights

Confirmed live in the last 24 hours

GitLab

GitLab

Remote, US
Remote
Posted April 17, 2026

Job Description

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.

The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software.

*Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab.

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
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