Senior Director, Data Analytics

GitLab

3h•Remote

About The Position

As the Senior Director, Data Analytics, you'll be the strategic analytics leader for Marketing and Product. You'll lead a newly combined organization that brings together data-driven insights across the customer lifecycle, from acquisition through adoption and expansion. Reporting to the Vice President, Enterprise Data, you'll partner closely with senior leaders to improve how teams make decisions, measure performance, and drive outcomes, with a focus on shared views of usage and consumption models and major product launches. You'll oversee two critical functions: Marketing Analytics (including demand generation, lifecycle marketing, brand, web, developer relations, localization, monetization, and campaign and event effectiveness) and Product Data Insights (including DevOps, Security, Platforms, AI products, new usage and consumption models, product adoption, feature usage, and customer behavior analysis).

Requirements

Strategic analytics leadership across both marketing analytics and product analytics, ideally in B2B SaaS or other high-growth technology environments.
Experience building, leading, and developing multi-layer analytics teams (including hiring, managing managers, and coaching leaders).
Ability to define and operationalize end-to-end measurement frameworks across Marketing and Product, including shared KPIs and clear metric definitions.
Strong analytical and technical skills, including SQL; statistical analysis and experimentation (A/B and multivariate testing); forecasting and scenario modeling; and advanced analytics techniques.
Experience with data visualization and BI tools (Tableau or similar), with a track record of building executive-ready reporting and narratives for senior leaders.
Proven partnership with Engineering and Data Engineering to translate business needs into telemetry, data models, and analytics requirements, and to improve reliability and delivery across the analytics stack.
Experience collaborating with Legal, Privacy, and Security partners to design compliant telemetry and data-collection approaches that respect regulations and customer expectations.
Ability to influence senior leaders through clear communication and actionable recommendations, and to work effectively in a fully remote, asynchronous environment while adopting GitLab's values and ways of working.

Responsibilities

Define and execute a unified analytics strategy across Marketing and Product, including shared metrics, measurement frameworks, and dashboards that serve as a single source of truth and connect marketing investment to product adoption, usage, and customer outcomes.
Build clear operating rhythms and ways of working that close historical gaps and help Marketing and Product make consistent, data-informed decisions.
Partner with Marketing and Product leadership, including the Chief Product & Marketing Officer and other senior stakeholders, to provide actionable insights and executive-ready recommendations that shape go-to-market plans, product launches, roadmap prioritization, and user experience improvements.
Solve complex analytics problems across both functions, including attribution modeling, lead scoring optimization, campaign and event effectiveness, product adoption and feature usage analysis, and analytics for AI-powered features (including instrumentation, usage, and cost drivers).
Build and maintain forecasting and scenario modeling frameworks in partnership with Finance, Product, and go-to-market leaders, tying pipeline, recurring revenue, and usage or consumption models to planning and investment decisions.
Establish and scale an experimentation program across Marketing and Product, setting standards for hypothesis design, test methodology, instrumentation requirements, and clear readouts that translate results into decisions.
Build strong partnerships with data engineering, engineering, and legal, privacy, and security teams to translate business questions into technical requirements, prioritize telemetry and data model work, and improve reliability, quality, accessibility, and compliance in the analytics stack.
Hire, mentor, and develop leaders and team members, raising the bar for strategic thinking, stakeholder partnership, and end-to-end ownership across the analytics organization.