GitLab is an open-core software company that develops the most comprehensive 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.
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. Co-create the future with us as we build technology that transforms how the world develops software.
As a Data Analyst, Customer Intelligence, you'll own the end-to-end development of customer-focused data products that help GitLab teams understand and improve the customer journey. You'll translate business questions from Go-To-Market and Product partners into clear requirements. You'll explore product usage and feedback data and turn findings into dashboards, reports, and recommendations that support better decisions across Sales, Marketing, Customer Success, Finance, and Product. Working within the Enterprise Data team, you'll collaborate closely with Data Engineers, Analytics Engineers, and Data Scientists. You'll experiment with GenAI tooling to increase speed to insight. You'll also advocate for data quality, security, and performance as you shape the long-term analytics strategy around our customers and their lifecycle.
What you’ll do- Collaborate with Go-To-Market, Product, and Enterprise Data teammates to translate business questions about the customer journey and product usage into clear analytical requirements.
- Design and build dashboards and reports that serve as a single source of truth and provide trusted visibility into customer lifecycle, behavior, and feedback.
- Explore and analyze data from sources such as GitLab.com, Salesforce, Zuora, Zendesk, Marketo, NetSuite, and Snowplow to uncover trends, risks, and opportunities for growth or improvement.
- Craft well-structured, maintainable visualizations in Tableau that follow internal standards and support decision-making at scale.
- Partner with Data Engineering and Analytics Engineering to define requirements for customer and product data models, shaping how data is collected, structured, and exposed.
- Experiment with generative AI tooling alongside the Data Platform team to enable conversational access to data products and reduce time to insight for stakeholders.
- Advocate for and contribute to improvements in data quality, security, and performance across the analytics lifecycle.
- Serve as a subject matter expert in data visualization and analysis by providing code reviews, pairing, and training to help other analysts deliver high-quality insights.
- Experience in analytics roles focused on SaaS products, including analyzing product usage, customer journeys, and lifecycle stages.
- Background combining data from multiple business systems (for example, marketing automation, product analytics, ERP, CRM) to create a unified view of the customer.
- Proficiency writing complex SQL queries with joins, aggregations, common table expressions, and conditional logic.
- Skill in designing and building business intelligence dashboards (such as in Tableau) that are maintainable, scalable, and aligned to stakeholder needs.
- Ability to translate complex business questions into clear analytical approaches, and to communicate findings and recommendations in a concise, accessible way.
- Experience collaborating with cross-functional partners such as Customer Success, Product, Marketing, Sales, and Finance in a remote, distributed environment.
- Attention to data quality, security, and performance, with a habit of documenting logic and edge cases clearly.
- Openness to experimenting with new tools, including generative AI, and to applying transferable skills from related analytics or data roles.
The Enterprise Data team partners with every department at GitLab to build and maintain trusted, scalable data products that inform strategic decisions across the business. As part of this team, the Customer Intelligence focus works closely with Data Engineers, Analytics Engineers, Data Scientists, and functional partners in Sales, Marketing, Finance, Customer Success, and Product to turn product usage and customer lifecycle data into actionable insights and self-serve dashboards. The team is fully remote and collaborates asynchronously across time zones, using shared standards, code reviews, and documentation to ensure consistency and quality. Current priorities include experimenting with GenAI-powered analytics experiences in partnership with the Data Platform team. For more on how this team works, see the Data Team Handbook Page.
The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary.
- 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
- Parental leave
- Home office support
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.
Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us.
GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know during the recruiting process.
