Data Analyst

• GitLab is an open-core software company that develops the AI-powered DevSecOps Platform used by more than 100,000 organizations. Our mission is to enable everyone to contribute to and co-create the software that powers our world. When everyone can contribute, consumers become contributors, significantly accelerating human progress. Our platform unites teams and organizations, breaking down barriers and redefining what\'s possible in software development. Thanks to products like Duo Enterprise and Duo Agent Platform, customers get AI benefits at every stage of the SDLC.\n• 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 and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems.\n• This role will specifically focus on collaborating with senior leaders, business stakeholders, and other members of the Data team to generate trusted analytics and insights to measure company performance, with expected outcomes of: reducing time to insight (making it faster and easier for internal users to find reporting for critical metrics) and increasing internal alignment (partnering with analysts & the data governance team to establish clear enterprise reporting definitions and documentation).\n• Responsibilities include delivering high-impact analytical insights, maintaining relationships with business stakeholders and leadership across the organization, collaborating with teams across finance, product, marketing, sales, and engineering to deliver integrated insights, partnering with Data team leadership to prioritize analytical work based on business impact, crafting analyses, reports, and dashboards that meet internal standards, experimenting with GenAI capabilities to improve data user experiences, contributing to long-range strategy and goals, advocating for data quality, security, and performance, serving as SME for data visualization and analysis, and supporting business teams to maximize value from customer and behavioral data.

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