GitLab - Vice President, Data & Insights
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 • How GitLab Supports Full-Time Employees • Benefits to support your health, finances, and well-being • Flexible Paid Time Off • Team Member Resource Groups • Equity Compensation & Employee Stock Purchase Plan • Growth and Development Fund • Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. • Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. • Country Hiring Guidelines:
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. • Data Platform Strategy and Roadmap • 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. • AI-Enabled Self-Service Analytics • 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. • Data Platform Engineering Leadership • 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. • Analytics Engineering and Semantic Layer • 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. • Consumption and Usage-Based Data Strategy • 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. • Data Governance and Quality • 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. • Executive and Cross-Functional Partnership • 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. • Team Leadership and Development • 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. • AI and Emerging Technology Adoption
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