Principal Product Manager, Engineering Intelligence & Insights

You will lead the product strategy for GitLab's next generation of engineering insight, helping software leaders, engineering managers, CTOs, and CPOs understand not just what their teams shipped, but why, and what to do next. As Principal Product Manager, Engineering Intelligence & Insights, you will shape how GitLab turns engineering data into decision-ready intelligence: the core data infrastructure and knowledge graph integrations that connect it, the out-of-the-box dashboards customers rely on today, and the conversational AI experiences that let leaders simply ask a question and get an answer instead of building a report. This is a high-impact role with broad scope across product and platform work. Success in your first year means setting a clear roadmap, aligning teams around the vision, and shipping insight experiences customers actually use to make better decisions, not just look at.

Projects in this space include building dashboards for DORA metrics, value stream performance, AI adoption, and AI cost and ROI analysis.
Projects in this space include developing conversational AI interfaces and extensible dashboard tooling on top of GitLab's analytics platform.

• Define the multi-horizon roadmap for GitLab's data analytics and insights platform, balancing immediate customer needs with long-term platform investment and setting clear success measures for roadmap delivery and customer adoption.
• Partner with engineering leaders to shape core platform capabilities, including data pipelines, storage, and APIs, that support analytics experiences across GitLab.
• Collaborate with the Knowledge Graph product team so insight experiences are powered by connected, cross-lifecycle data rather than isolated project metrics.
• Design a tiered analytics experience that meets customers where they are: conversational AI discovery for a fast answer, out-of-the-box dashboards for recurring needs, and custom dashboard creation for teams that want full control. Reduce time to insight as customers grow.
• Prioritize dashboards and insight workflows for software leaders so they can measure deployment frequency, cycle time, value stream management, AI feature impact, and AI cost and ROI in GitLab.
• Champion the needs of engineering leaders and executive users, translating how they actually consume data, often live in a meeting under time pressure, into product decisions and roadmap priorities.
• Enable internal teams such as sales, customer success, and data engineering to build, share, and use dashboards that support customer-facing work and improve the speed and consistency of customer reporting.
• Drive a clear and consistent analytics narrative across product, marketing, and analyst conversations through close cross-functional partnership, improving launch readiness and market understanding.

• Experience defining product vision and driving execution across complex, multi-team product programs.
• Background building analytics, dashboard, or business intelligence products for software engineering, DevOps, or technical leadership users.
• Knowledge of the software development lifecycle and common engineering performance measures such as DORA metrics, value stream metrics, and cycle time.
• Working understanding of data infrastructure, data pipelines, APIs, and business intelligence tooling, with the ability to partner effectively with data engineering teams.
• Ability to turn ambiguous customer problems into clear product requirements, prioritization decisions, and roadmap direction.
• Skill influencing across engineering, design, sales, customer success, and data teams in a distributed environment without relying on formal authority.
• Familiarity with AI-powered analytics experiences, conversational interfaces, knowledge graph concepts, or related data exploration approaches.
• Comfort bringing transferable experience from adjacent product areas if you have worked on technically complex products and can speak fluently about data and customer workflows.

This team builds the analytics and insights capabilities that help customers understand software delivery performance within GitLab. The work spans platform foundations and user-facing experiences, bringing together product, engineering, and partner teams to support dashboards, connected data, and emerging AI-based ways to explore insight. The team works asynchronously across regions and collaborates closely with adjacent groups, including data-focused platform teams and the Knowledge Graph team, to solve a shared challenge: turning complex engineering data into clear, useful information for technical and executive decision-makers.