Senior Data Analyst, Enterprise Analytics

About This RoleAI processing…

Key Responsibilities

• 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.
• 6
  Partner with Revenue Operations, Finance, and go-to-market analysts and stakeholders to define questions, align on metric definitions and pacing logic, and deliver dashboards and deep-dive analyses.
• 7
  Present insights in a clear, actionable way for both operational and executive audiences so teams can make better decisions faster.
• 8
  Share best practices in SQL, data visualization, and go-to-market analytics , including code reviews and pairing support on high-priority dashboards.

Requirements

• Strong analytical skills with the ability to frame ambiguous business questions, structure analysis, and translate findings into clear recommendations for go-to-market and executive stakeholders .
• 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.
• Alignment with GitLab's values and openness to applying transferable skills from related analytics, revenue operations, or business intelligence roles.
• Experience with dbt and modern analytics engineering patterns, including trusted marts, certified sources, and documented lineage, is helpful but not required.

Perks & Benefits