Revenue Operations Analyst

About The Role The role sits at the intersection of revenue data, GTM systems, and business process — owning the pipelines, dashboards, and analyses that sales, marketing, and finance leaders use to make decisions. This is a hands, CRM architecture (Salesforce), forecast integrity, funnel analytics, and the operational machinery behind quota and territory planning. You will partner closely with sales leadership, RevOps engineers, and finance to turn messy revenue data into reliable reporting and process improvements. The work directly shapes how the go-to-market organization forecasts, prioritizes accounts, and measures performance. Key Responsibilities Build and maintain revenue reporting in Salesforce, Tableau/Looker, and SQL-based pipelines covering pipeline generation, conversion, and forecast accuracy Own weekly and quarterly forecast processes: validate pipeline hygiene, reconcile CRM data against finance models, and flag risks with supporting analysis Design and run territory, quota, and book-of-business analyses to support annual planning and mid-year rebalancing Investigate and resolve data integrity issues across Salesforce, marketing automation, and billing systems (e.g., HubSpot, NetSuite, Chargebee) Partner with sales and marketing leadership on funnel diagnostics — identify stage conversion drop-offs and quantify the revenue impact of proposed fixes Administer and document CRM processes, including lead routing, opportunity stage definitions, and validation rules, in partnership with Salesforce admins Deliver executive-ready dashboards and ad hoc analyses for board reporting, QBRs, and planning cycles What We Are Looking For 3-6 years of experience in revenue operations, business analysis, sales operations, or a comparable analytics-heavy role, ideally in B2B SaaS Strong SQL skills and hands‑on experience with a BI tool (Tableau, Looker, or Power BI) Deep working knowledge of Salesforce — reporting, data models, and common RevOps workflows (Clari, Gong, Outreach experience a plus) Demonstrated ability to translate business questions into analyses and recommendations, not just dashboards Comfort operating with ambiguity across sales, marketing, and finance stakeholders Bachelor's degree in a quantitative field (economics, finance, statistics, or similar) or equivalent practical experience Bonus: experience with revenue recognition concepts, Python/R for analysis, CPQ implementations, or building dbt models / working with a modern data stack #J-18808-Ljbffr