Sales Analytics Manager

As the Sales Analytics Manager, you’ll be the go-to individual contributor for turning complex sales and go-to-market data into clear insights and tools that help leaders make better decisions. You’ll work with pipeline, quota, and core sales performance metrics to build analytics, dashboards, and reporting that Field Operations stakeholders can rely on. You’ll own projects end to end: partnering with stakeholders to understand questions, managing projects, running the analysis, and translating results into recommendations that drive tangible impact. You’ll work primarily with Tableau, SQL, and Python. You’ll also engage with modern data stack components like data warehouse and modeling tools such as Snowflake and dbt, and you’ll collaborate closely with adjacent functions such as Customer Success analytics. Over your first year, you’ll focus on establishing a strong analytics foundation for sales, delivering quick-win insights and scalable reporting, and becoming a trusted partner to leaders across the go-to-market organization.

• Lead end-to-end sales analytics work, from defining questions with stakeholders to building datasets, analysis, and clear recommendations that inform sales decisions.
• Develop and maintain reporting and dashboards in Tableau and other reporting tools that surface pipeline, quota, and core sales performance metrics to sales and leadership teams.
• Drive deep analysis of sales pipeline, quota attainment, and other sales metrics using SQL and Python to uncover trends, risks, and opportunities.
• Collaborate closely with Sales, Field Operations / RevOps, Finance, and Customer Success partners to translate business needs into scalable analytical solutions and tools.
• Own the quality, structure, and usability of sales data in partnership with central data teams, ensuring consistency across Snowflake, dbt models, and other data sources where relevant.
• Manage stakeholder expectations and project timelines, prioritizing requests and communicating trade-offs and outcomes in a clear, structured way.
• Partner with Customer Success and broader go-to-market teams to align sales analytics with go-to-market and customer success metrics where needed.
• Contribute to improving analytics processes, documentation, and standards so the team can work more efficiently and reuse high-impact analytical assets.

• Background working in sales analytics, including hands-on experience with pipeline, quota, and core sales performance metrics.
• Proficiency with business intelligence tools, with direct experience using Tableau or a similar BI platform and the ability to adapt to GitLab’s tooling.
• Practical skills in querying and transforming data using SQL and Python, and comfort working with modern data warehouses and analytics environments.
• Ability to manage projects and stakeholders, translating business questions into analytical plans and communicating findings to non-technical partners.
• Experience supporting sales or go-to-market teams, with familiarity in areas such as customer success, pre-sales, post-sales, or partner / channel motions.
• Exposure to tools and concepts such as dbt, Snowflake, or comparable technologies, and an understanding of data structures that support scalable reporting.
• Clear, structured communication skills in an all-remote, asynchronous environment, including documenting work and collaborating across time zones.
• Openness to learning GitLab’s product, data model, and ways of working, with transferable experience from sales, revenue, or field operations analytics roles.

The Revenue Analytics team sits within GitLab’s Revenue Strategy & Operations organization and focuses on turning sales and go-to-market data into clear, actionable insights for leaders and frontline teams. You’ll join a distributed group that partners closely with Sales, Customer Success, Finance, and other Revenue Operations team members to understand pipeline health, quota performance, and broader go-to-market metrics, and to build the tools and reporting that support better decisions. The team works asynchronously across time zones, using GitLab and our data stack to collaborate on projects, share context, and maintain transparency. Current priorities include strengthening our sales analytics foundation, deepening our use of business intelligence tools like Tableau, and building repeatable analytics that help stakeholders quickly understand performance and identify opportunities to improve results.