GitLabData Analyst, Product
An overview of this role
As a Product Data Analyst on GitLab's Product Data Insights team, you'll help product teams make better decisions through trusted data and clear analysis. Working closely with Product Managers, Engineering, UX, and leadership, you'll examine customer behavior across the customer journey to improve both the customer experience and business outcomes. In this role, you'll build business intelligence solutions, define and maintain product key performance indicators, and turn usage data into insights that support strategic decisions.
This role focuses on GitLab's Platforms sections, an important area that helps ensure GitLab's infrastructure can scale over time. You'll also support our Dedicated offering by exploring usage and behavioral patterns across that deployment type. In GitLab's all-remote, asynchronous environment, you'll contribute to a transparent, values-driven culture where data storytelling helps teams understand product health and act with confidence.
What you'll do
- Collaborate with stakeholders ranging from individual contributor Product Managers to leadership to understand business questions and define the right analytical approach.
- Gather data from multiple sources and connect disparate data points into a clear story about product usage, customer behavior, and product health.
- Establish reporting for new products and features, including defining metrics and building repeatable analysis that teams can use to track adoption and performance.
- Analyze usage patterns within GitLab's Platforms sections to help teams understand how this area is performing and where improvements may be needed.
- Explore behavioral trends for the Dedicated offering to surface insights that can inform product decisions and the customer experience.
- Partner with UX to better understand user behavior and support research with quantitative analysis.
- Work with Engineering teams on data collection and instrumentation approaches so product usage can be measured accurately and consistently.
- Collaborate with Analytics Engineers on data modeling needs for reporting and analysis, helping ensure the underlying data supports reliable decision-making.
What you'll bring
- Advanced SQL skills and the ability to use data to answer complex product questions with clarity and accuracy.
- Experience building business intelligence visualizations and dashboards, ideally in Tableau or a similar tool.
- Experience working directly with Product and Engineering teams on data creation, instrumentation, and measurement strategy.
- Experience partnering with Data and Analytics Engineering teams to shape data models for reporting and product analysis.
- Strong analytical thinking and the ability to turn product usage data into practical recommendations for stakeholders at different levels.
- Experience conducting and interpreting A/B tests to evaluate product changes and support evidence-based decisions.
- Clear written and verbal communication skills, with the ability to explain complex findings in simple language.
- Comfort working in an all-remote, asynchronous environment and collaborating effectively across functions while staying aligned with GitLab's values.
- Full Job Description
About the team
The Product Data Insights team sits within GitLab's Enterprise Data & Insights organization and includes a manager and product analysts who support specific areas of the product. As a team, we work closely with product partners to improve decision-making through trusted metrics, thoughtful analysis, and clear storytelling. Our work helps teams understand product usage, customer behavior, and overall product health so they can make informed decisions that improve GitLab.
You'll join a distributed team that values transparency, collaboration, and strong partnership with cross-functional stakeholders. The team supports a range of product areas, and this role will be closely connected to the Platforms sections and the Dedicated offering. It's a strong fit for someone who enjoys working across teams, building context in a complex product environment, and helping others use data with confidence.