GitLab - Principal Product Manager, Engineering Intelligence & Insights
Requirements
• 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. • How GitLab Supports Full-Time Employees • Benefits to support your health, finances, and well-being • Flexible Paid Time Off • Team Member Resource Groups • Equity Compensation & Employee Stock Purchase Plan • Growth and Development Fund • Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. • Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. • Country Hiring Guidelines:
Responsibilities
• 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.
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