Director of Engineering, Analytics Platform & Products

An overview of this role

As Director of Engineering, Analytics Platform & Products you will lead the engineering strategy, architecture, and execution for GitLab's Analytics stage. This organization powers GitLab's analytics ecosystem end to end, from instrumentation and telemetry through data movement, storage, and serving, to customer-facing analytics experiences. You will help shape how GitLab and its customers measure adoption, engineering health, and business impact across SaaS, self-managed, and air-gapped deployments. Reporting into senior engineering leadership, you will lead through Engineering Managers and partner closely with Principal Engineers, Product, Data, and AI leaders to set a multi-year direction and build the next generation of analytics platforms and data products.

You will have broad scope across data platforms, product analytics, and distributed systems, with clear ownership for team health, technical direction, and delivery. In your first year, you'll guide the roadmap across instrumentation, data foundations, and data products, strengthen the architecture that supports multiple deployment models, and help scale the organization as we continue to invest in new analytics capabilities.

What you’ll do

• Lead the Analytics engineering organization with accountability for strategy, architecture, execution, and team health, with success measured through roadmap delivery, service reliability, and organizational effectiveness.
• Guide Engineering Managers and partner with Principal Engineers to set technical direction and support key architectural decisions.
• Define the roadmap for analytics capabilities across instrumentation, data foundations, and customer-facing data products, with success measured through adoption, usage, and customer value.
• Oversee the design and operation of end-to-end data pipelines, including instrumentation, ingestion, transformation, storage, serving, and product integration, with accountability for data quality, freshness, latency, and reliability.
• Drive platform and architecture decisions that support GitLab's SaaS, self-managed, and regulated or isolated deployment environments.
• Collaborate with Product, UX, Infrastructure, Data, and AI leaders to align roadmap, architecture, and execution.
• Build a high-performing engineering organization with clear ownership, strong operational discipline, and a consistent technical standard that improves delivery predictability, operational health, and technical quality.
• Champion asynchronous ways of working and AI-assisted development workflows that increase engineering focus, throughput, and delivery quality.

What you’ll bring

• Experience leading multiple engineering teams through managers in a Director-level or comparable engineering leadership role.
• Strong knowledge of distributed systems and large-scale platform engineering.
• Deep understanding of end-to-end data pipelines, analytics platforms, and the technical tradeoffs involved in building them.
• Ability to engage deeply in architecture, system design, and technical discussions with senior and principal engineers.
• Experience delivering platforms across SaaS, self-managed, and regulated or isolated environments.
• Commitment to engineering practices such as test-driven development, continuous delivery, and modular architecture.
• Strong cross-functional communication and leadership skills in a distributed, remote-first environment.
• Interest in transferable experience from adjacent areas such as product analytics, instrumentation, observability, or privacy-conscious analytics systems.

About the team

The Analytics Stage team owns GitLab's analytics platform and analytics product surface. The organization includes Data Products, Instrumentation, and Data Foundations, and builds the systems that turn product, usage, billing, and cost data into trusted instrumentation, scalable data foundations, queryable APIs, dashboards, and customer-facing analytics experiences. We work asynchronously across regions and partner closely with Product, Data, UX, Infrastructure, and AI to solve challenges in scale, privacy, reliability, and deployment flexibility across SaaS, self-managed, and air-gapped environments. For more on how we work, see the team page.