Senior Data Analyst, Enterprise Analytics

GitLab GitLab · Enterprise · India · Data

Senior Data Analyst on the Enterprise Analytics team at GitLab, supporting go-to-market and executive reporting. The role involves working with sales, marketing, revenue operations, and finance to deliver company-level reports, performance views, and lifecycle reporting. Key tools include Snowflake, dbt, Tableau, and VS Code. The analyst will also improve documentation and data foundations.

What you'd actually do

  1. Build and maintain executive-facing scorecards, go-to-market performance views, and new-customer reporting that connect pipeline, bookings, and product usage signals into targets-versus-actuals tracking by motion.
  2. Design performant, reusable Tableau Cloud data sources and help shape the underlying dbt models so reporting layers are stable, governed, and aligned to single-source-of-truth patterns.
  3. Collaborate with Analytics Engineering and Data Engineering to improve dbt models that support reliable, scalable reporting for business stakeholders.
  4. Document metric logic, data lineage, and Tableau usage patterns in the handbook so stakeholders can understand how data products are built and used.
  5. Implement and monitor data quality checks and reconciliations across Snowflake, Salesforce, and other go-to-market systems to strengthen trust in company-level reporting.

Skills

Required

  • Advanced SQL skills working with large, complex data models, preferably in Snowflake, including joining many tables and building reusable queries and views.
  • Proven experience building executive-facing dashboards in Tableau or a similar business intelligence tool, including data source design, performance tuning, and visualization best practices.
  • Deep understanding of go-to-market concepts such as new-customer and first-order metrics, pipeline, bookings, Net ARR, go-to-market motions, sales segments, and marketing funnel metrics.
  • Strong command of GenAI tools for daily use in your work and the judgment to use them effectively to improve speed and quality.
  • Ability to communicate complex analyses in a clear, concise way through presentations, written narratives, and data visualizations for both technical and non-technical audiences.
  • Comfort working in an all-remote, asynchronous environment, with a high level of ownership and the ability to drive work forward independently.

Nice to have

  • Experience with dbt and modern analytics engineering patterns, including trusted marts, certified sources, and documented lineage, is helpful but not required.

What the JD emphasized

  • Strong command of GenAI tools for daily use in your work and the judgment to use them effectively to improve speed and quality.