Revenue Operations Analyst

Overview

This role sits at the intersection of data, systems, and go-to-market execution. Responsibilities include building reporting, forecasting, and process infrastructure that sales, marketing, and finance teams rely on to make decisions.

You will help lead pipeline analytics, CRM health, and revenue forecasting by turning messy data from Salesforce, HubSpot, and internal systems into dashboards and insights.

Responsibilities

• Build and maintain revenue dashboards in Looker, Tableau, or Power BI covering pipeline coverage, conversion rates, rep performance, and forecast accuracy
• Administer and optimize Salesforce, managing objects, fields, validation rules, and automation using Flow or Process Builder to keep CRM data clean and adoption high
• Own weekly and monthly forecasting, reconciling sales-provided numbers against actuals and modeling scenarios in Excel or SQL
• Partner with sales, marketing, and finance leadership on territory design, quota planning, and compensation model analysis
• Write SQL queries and build ETL workflows (dbt, Airflow, or similar) to unify data from Salesforce, HubSpot, billing systems, and product databases
• Evaluate and implement go-to-market tooling, including enrichment, routing, attribution, and enablement platforms; handle vendor selection and rollout management
• Document and improve lead-to-revenue processes, identifying friction points and shipping measurable fixes

Requirements

• 3–6 years of revenue operations, sales operations, or business analysis experience, ideally in B2B SaaS
• Advanced Salesforce administration skills (clean data models, automation, reporting); Salesforce Admin certification is a plus
• Strong SQL skills and comfort building analyses from raw data; hands-on experience with a BI tool (Looker, Tableau, or Power BI)
• Experience supporting forecasting, quota, or territory planning processes with finance or sales leadership
• Deep Excel or Google Sheets modeling skills, with the ability to clearly communicate analysis to executives
• Bachelor’s degree in a quantitative field (economics, finance, statistics, engineering) or equivalent practical experience

Preferred Qualifications

• Bonus: experience with Python or R for analysis
• Bonus: experience with dbt/ETL tooling
• Bonus: experience with CPQ or billing systems
• Bonus: experience building go-to-market tech stacks from scratch