Senior Revenue Analytics Analyst - GitLab

About the Role

As a Senior Revenue Analytics Analyst, you will partner with global Sales Strategy, Solutions Architect, and Ecosystem teams to optimize pre-sales motions, product trials, and partner-driven consumption. You will translate complex business questions into analytical requirements, build AI-driven tools, and maintain the data foundations that power GitLab's go-to-market strategy.

What You'll Do

• Strategic Partnership: Collaborate with Go-To-Market stakeholders to translate business needs into clear analytical requirements regarding pipeline, consumption, and sales efficiency.
• Solution Design: Build AI and analytic solutions to provide actionable insights for trial management, win rates, and sales performance.
• Data Modeling: Partner with operational teams to define data requirements, ensuring high-quality, consistent data models across Snowflake and dbt.
• Advanced Analysis: Utilize segmentation, cohort analysis, and A/B testing to inform engagement strategies and forecast the impact of digital programs.
• Subject Matter Expertise: Serve as a technical lead, documenting methodologies and mentoring team members on best practices for sales analytics.

What You'll Bring

• Proven experience in analytics roles within SaaS, specifically focusing on pre-sales motions and customer lifecycle health.
• Proficiency in writing complex SQL queries (CTEs, window functions, conditional logic).
• Experience using Python for data analysis and trend discovery.
• Ability to synthesize data from multiple GTM systems into a unified view.
• Strong communication skills with the ability to present technical findings to both technical and non-technical stakeholders.
• Experience working in a distributed, remote-first environment.
• A proactive mindset toward experimenting with generative AI and new analytical tooling.

About the Team

The Revenue Analytics team is part of GitLab’s Revenue Strategy & Operations organization. We focus on turning GTM data into actionable insights. We work asynchronously across time zones, maintaining transparency and high standards for our data stack, including Tableau, Snowflake, and dbt.