Vice President, Data & Insights

About the role

GitLab is seeking a Vice President 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 will own the end-to-end strategy and delivery of our data ecosystem, defining the roadmap for certified datasets, clean schema architecture, and AI-ready infrastructure. You will lead a distributed team of data platform engineers, analytics engineers, data governance specialists, and embedded analysts, guiding them to evolve from reactive reporting to proactive, AI-enabled insight generation. In this role, you will act as a trusted advisor to executive leadership, translating complex data strategy into actionable plans that accelerate digital transformation across the business. You will drive the adoption of AI as a core productivity multiplier, ensuring all team members leverage these tools to deliver higher impact. This position represents a transformational opportunity to move GitLab beyond traditional dashboards toward a self-service data organization where stakeholders access trusted insights on demand. You will build the certified data foundations that power intelligent, consumption-aware decisions across the company and help define how the data organization is recognized as a strategic partner.

Key facts

What you'll do

• Define and execute a multi-year enterprise data platform strategy, prioritizing certified datasets, clean schema architecture, and scalable infrastructure to support AI-native consumption and self-service access.
• Lead the transformation toward AI-enabled self-service analytics, enabling business stakeholders to perform analysis and access insights independently while empowering the data team to focus on high-value strategic work.
• Own 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 upon.
• Drive analytics engineering practices that produce governed, well-documented, and reusable data models, championing the shift from ad hoc dashboard production to curated data products that serve as a single source of truth.
• Develop deep expertise in GitLab's consumption and usage-based business model, ensuring the data organization delivers the metrics, trends, and signals that matter most to Revenue, Finance, and Product stakeholders.
• 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.
• Serve as a strategic thought partner to leaders across Sales, Finance, Product, and People, translating complex data questions into scalable answers and building strong cross-functional relationships.
• Inspire and develop a high-performing, distributed team across data platform, analytics engineering, governance, and analysis, fostering continuous learning and career growth.
• Collaborate closely with the CIO and executive team to align data initiatives with enterprise priorities, ensuring that data and AI investments directly support organizational goals.
• Promote a culture of experimentation and evidence-based decision-making, enabling stakeholders to leverage insights on demand and continuously refine how GitLab measures and learns from its operations.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Statistics, Mathematics, or a related quantitative field or equivalent practical experience.
• 15+ years of progressive experience in data, analytics, or technology leadership roles, with a demonstrated track record of building and scaling data organizations.
• 5+ years of experience managing and developing data platform and analytics engineering teams in a distributed or remote environment.
• Deep expertise in data architecture, including modeling, warehousing, pipelines, and consumption patterns for enterprise-scale platforms.
• Proven experience delivering AI-enabled analytics and self-service data models that support business users in making data-driven decisions.
• Strong knowledge of data governance, quality frameworks, and best practices for lineage, documentation, and access control.
• Experience working with consumption-based business models and usage analytics in a SaaS environment.
• Excellent communication and influence skills, with the ability to partner with executive leadership and translate business needs into data strategy.

Nice to have

• Experience with modern data stack components including cloud data warehouses, orchestration tools, and semantic layer technologies.
• Familiarity with AI and machine learning workflows in data platforms, including MLOps concepts and model consumption patterns.
• Background in DevOps practices for data infrastructure and CI/CD pipelines for analytics code.

Practical notes

This is a full-time remote position based in the United States. The role requires regular availability during standard business hours to collaborate with global teams. No specific travel requirements are expected. Visa sponsorship may be considered for eligible candidates. The position is subject to applicable employment laws and regulations in the candidate's country of residence.