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

An overview of this role

As a Senior Data Analyst, Marketing Analytics at GitLab, you'll serve as a strategic analytics partner to Marketing leadership and help shape how we measure, model, and improve marketing performance. Reporting to the Senior Manager of Marketing Analytics, you'll take ownership of high-impact analytical work across attribution, inbound funnel analysis, target setting, and campaign measurement. You'll work across the full data lifecycle, from building and maintaining dbt models in Snowflake that power business intelligence, to delivering executive-ready insights, to partnering cross-functionally to support important business decisions. In this role, you'll use a modern analytics and AI-enabled workflow that includes Snowflake, Claude with MCP connections, and GitLab Duo Agent Platform in git-based team workflows. This is a high-visibility role for someone with strong SQL skills, sound judgment in B2B software marketing analytics, and the ability to turn complex data into clear stories for senior stakeholders in our all-remote, values-driven environment.

What you'll do

• Serve as a trusted advisor to senior Marketing and Developer Relations leaders, providing data-driven insights that inform marketing strategy, product development, and go-to-market decisions.
• Establish and scale proactive insights across the Marketing function, including experimentation and connecting marketing credit from initial touchpoints to annual recurring revenue.
• Measure the impact of community programs, developer advocacy, and evangelism efforts on awareness, adoption, and pipeline.
• Evaluate the effectiveness of demand generation programs, including trial conversion analysis across segments, lead scoring optimization, and outreach platform performance.
• Partner closely with Analytics Engineering and Data Platform teams to translate business questions into clear technical requirements and support reliable delivery in the analytics stack.
• Help evolve GitLab's multi-touch attribution approach, including attributed metric definitions and implementation across reporting.
• Contribute to annual planning cycles through partnership with Sales, Finance, and Product leadership.
• Use AI-enabled analytics workflows through GitLab Duo Agent Platform, Claude with MCP integrations, and Glean within GitLab to improve how insights are developed and shared.

What you'll bring

• 5+ years of experience in a data analyst or analytics engineer role, preferably in B2B software marketing analytics or in a large-scale analytics consultancy supporting similar companies.
• Strong proficiency in SQL, including the ability to connect disparate data sources and build a clear view of marketing program performance in a cloud data warehouse, ideally Snowflake.
• Experience working with senior leaders and tailoring data-driven narratives to support decision-making.
• Hands-on experience with dbt for data transformation, testing, and documentation.
• Strong understanding of B2B marketing funnel metrics, including marketing qualified leads, sales accepted opportunities, pipeline, multi-touch attribution, and conversion rate analysis.
• Experience working with marketing automation platforms such as Marketo and customer relationship management systems such as Salesforce, including data integration patterns and sync logic.
• Proficiency with a business intelligence and visualization tool, with Tableau preferred.
• Excellent written and verbal communication skills, with the ability to distill complex analysis into clear narratives for technical and non-technical audiences.
• Experience with AI-assisted analytics development, including MCP connections and agentic workflows.
• Familiarity with Git workflows for version control, continuous integration and continuous delivery, issue tracking, and merge request workflows.
• Comfort working in a remote, async-first, globally distributed environment.
• We know it's tough to match every qualification exactly, so if you're excited about this role, we encourage you to apply.

About the team

The Marketing Analytics team sits within GitLab's Enterprise Data organization and partners closely with the broader Marketing team as well as other departments across GitLab. We build and maintain trusted, scalable data products that help inform strategic decisions for Marketing while also creating alignment with related business metrics, especially across Product and Sales. You'll join a fully remote team that collaborates asynchronously across time zones using our shared standards, code review, and documentation to support consistency and quality. We work on analytically complex, high-impact problems where strong data foundations, clear definitions, and thoughtful cross-functional partnerships are essential to helping stakeholders understand performance and make better decisions.

An overview of this role

As a Senior Data Analyst on GitLab's Enterprise Analytics team, you'll support some of GitLab's most visible go-to-market and executive reporting. You'll work closely with Sales, Marketing, Revenue Operations, Finance, and analytics partners to deliver company-level reports, go-to-market performance views, and lifecycle reporting that leaders use to run the business. Working in Snowflake, dbt, Tableau, and VS Code, you'll turn ambiguous business questions into trusted, well-documented data products that serve as a single source of truth for performance and targets versus actuals. You'll also help improve our Enterprise Analytics handbook and core data foundations so strategy, processes, and metric definitions are clear and usable in our all-remote, values-driven environment.

What you'll do

• Build and maintain executive-facing scorecards, go-to-market performance views, and new-customer reporting that connect pipeline, bookings, and product usage signals into targets-versus-actuals tracking by motion.
• Design performant, reusable Tableau Cloud data sources and help shape the underlying dbt models so reporting layers are stable, governed, and aligned to single-source-of-truth patterns.
• Collaborate with Analytics Engineering and Data Engineering to improve dbt models that support reliable, scalable reporting for business stakeholders.
• Document metric logic, data lineage, and Tableau usage patterns in the handbook so stakeholders can understand how data products are built and used.
• Implement and monitor data quality checks and reconciliations across Snowflake, Salesforce, and other go-to-market systems to strengthen trust in company-level reporting.
• Partner with Revenue Operations, Finance, and go-to-market analysts and stakeholders to define questions, align on metric definitions and pacing logic, and deliver dashboards and deep-dive analyses.
• Present insights in a clear, actionable way for both operational and executive audiences so teams can make better decisions faster.
• Share best practices in SQL, data visualization, and go-to-market analytics, including code reviews and pairing support on high-priority dashboards.

What you'll bring

• Strong analytical skills with the ability to frame ambiguous business questions, structure analysis, and translate findings into clear recommendations for go-to-market and executive stakeholders.
• Advanced SQL skills working with large, complex data models, preferably in Snowflake, including joining many tables and building reusable queries and views.
• Proven experience building executive-facing dashboards in Tableau or a similar business intelligence tool, including data source design, performance tuning, and visualization best practices.
• Deep understanding of go-to-market concepts such as new-customer and first-order metrics, pipeline, bookings, Net ARR, go-to-market motions, sales segments, and marketing funnel metrics.
• Strong command of GenAI tools for daily use in your work and the judgment to use them effectively to improve speed and quality.
• Ability to communicate complex analyses in a clear, concise way through presentations, written narratives, and data visualizations for both technical and non-technical audiences.
• Comfort working in an all-remote, asynchronous environment, with a high level of ownership and the ability to drive work forward independently.
• Alignment with GitLab's values and openness to applying transferable skills from related analytics, revenue operations, or business intelligence roles.
• Experience with dbt and modern analytics engineering patterns, including trusted marts, certified sources, and documented lineage, is helpful but not required.

About the team

The Enterprise Analytics team is a centralized, cross-functional partner to GitLab's go-to-market organization and executive leadership. The team turns data from systems such as Snowflake, Salesforce, GitLab, and other business platforms into actionable insights and self-service reporting that support operating reviews and strategic decision-making. You'll join a fully remote, globally distributed team that collaborates asynchronously to define shared metrics and deliver reporting that leaders can trust. We document our strategy and processes in the handbook so stakeholders can use data more independently. The team is currently focused on scaling company-level scorecards, new-customer and first-order reporting, and go-to-market performance analytics across motions.