Director of Engineering, Analytics Platform & Products

<div class="content-intro"><p>GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.</p> <p>The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values&nbsp;and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. <a href="https://www.youtube.com/watch?v=OuZIb5zszQI">Co-create the future with us</a> as we build technology that transforms how the world develops software.</p> <p>*<em>Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab.</em></p></div><h3>An overview of this role</h3> <p>As <span class="textBold">Director of Engineering, Analytics Platform &amp; Products</span>&nbsp;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.</p> <p>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.</p> <h3>What you’ll do</h3> <ul> <li value="1"><span class="textBold">Lead</span> the Analytics engineering organization with accountability for strategy, architecture, execution, and team health, with success measured through roadmap delivery, service reliability, and organizational effectiveness.</li> <li value="2"><span class="textBold">Guide</span> Engineering Managers and partner with Principal Engineers to set technical direction and support key architectural decisions.</li> <li value="3"><span class="textBold">Define</span> the roadmap for analytics capabilities across instrumentation, data foundations, and customer-facing data products, with success measured through adoption, usage, and customer value.</li> <li value="4"><span class="textBold">Oversee</span> 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.</li> <li value="5"><span class="textBold">Drive</span> platform and architecture decisions that support GitLab's SaaS, self-managed, and regulated or isolated deployment environments.</li> <li value="6"><span class="textBold">Collaborate</span> with Product, UX, Infrastructure, Data, and AI leaders to align roadmap, architecture, and execution.</li> <li value="7"><span class="textBold">Build</span> 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.</li> <li value="8"><span class="textBold">Champion</span> asynchronous ways of working and AI-assisted development workflows that increase engineering focus, throughput, and delivery quality.</li> </ul> <h3>What you’ll bring</h3> <ul> <li value="1"><span class="textBold">Experience</span> leading multiple engineering teams through managers in a Director-level or comparable engineering leadership role.</li> <li value="2"><span class="textBold">Strong knowledge</span> of distributed systems and large-scale platform engineering.</li> <li value="3"><span class="textBold">Deep understanding</span> of end-to-end data pipelines, analytics platforms, and the technical tradeoffs involved in building them.</li> <li value="4"><span class="textBold">Ability</span> to engage deeply in architecture, system design, and technical discussions with senior and principal engineers.</li> <li value="5"><span class="textBold">Experience</span> delivering platforms across SaaS, self-managed, and regulated or isolated environments.</li> <li value="6"><span class="textBold">Commitment</span> to engineering practices such as test-driven development, continuous delivery, and modular architecture.</li> <li value="7"><span class="textBold">Strong cross-functional communication</span> and leadership skills in a distributed, remote-first environment.</li> <li value="8"><span class="textBold">Interest in transferable experience</span> from adjacent areas such as product analytics, instrumentation, observability, or privacy-conscious analytics systems.</li> </ul> <h3>About the team</h3> <p>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 <a href="https://handbook.gitlab.com/handbook/engineering/data-engineering/analytics/" target="_blank">the team page</a>.&nbsp;</p><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p><em>The base salary range for this role’s listed level is currently for residents of the&nbsp;United States only.