Revenue Operations Analyst — Phoenix, AZ

About The Role

The role owns the revenue data layer and the systems behind it: CRM hygiene, pipeline analytics, forecasting models, and the reporting that sales, marketing, and finance leaders use to make decisions.

This is a high-leverage position at the intersection of data and go-to-market execution — the work directly shapes how pipeline is prioritized, how forecasts are built, and where operational friction gets removed.

Key Responsibilities

• Own CRM data quality and process design in Salesforce, including lead routing, stage definitions, validation rules, and automation via Flow

• Build and maintain dashboards in Salesforce Reports, Looker, or Tableau covering pipeline coverage, conversion rates, rep productivity, and forecast accuracy

• Partner with finance and sales leadership on quarterly forecasting, producing models that reconcile CRM pipeline with actual bookings

• Analyze funnel performance across marketing, SDR, and AE motions; surface insights and recommendations to GTM leadership

• Evaluate, implement, and administer revenue tech stack tools (e.g., Gong, Outreach, Clari, ZoomInfo), including onboarding and adoption tracking

• Document and enforce RevOps processes — quote-to-cash handoffs, territory assignments, and renewal workflows — with clear SOPs

• Run territory planning, quota setting support, and comp plan modeling during annual planning cycles

What We Are Looking For

• 3-6 years in revenue operations, sales operations, business analysis, or a comparable data-heavy GTM role

• Advanced Salesforce administration skills (reports, dashboards, Flow automation); admin certification a plus

• Strong SQL skills and hands-on experience with a BI tool (Looker, Tableau, or Power BI)

• Demonstrated ability to build forecasting or pipeline models in Excel or Google Sheets at an expert level

• Experience partnering with sales and finance leaders and translating ambiguous business questions into analytical deliverables

• Bachelor's degree in a quantitative field (economics, statistics, engineering, finance) or equivalent practical experience

• Bonus: experience with dbt or a modern data stack, Python for analysis, CPQ implementation, or supporting a company through rapid headcount growth