Revenue Operations Analyst — Chicago, IL

About The Role

The role sits at the center of the go-to-market engine: owning the data, systems, and reporting that sales, marketing, and customer success teams rely on to make decisions.

You will manage and improve the revenue tech stack (CRM, marketing automation, BI), build reliable pipeline and forecast analytics, and turn messy operational questions into clean, actionable metrics.

Key Responsibilities

• Administer and optimize the CRM (Salesforce or HubSpot), owning object architecture, validation rules, and workflow automation

• Build and maintain dashboards in Looker, Tableau, or SQL-backed BI tools covering pipeline, conversion, forecast accuracy, and rep performance

• Own lead-to-revenue data flows, including lead routing, enrichment, deduplication, and lifecycle-stage hygiene across systems

• Partner with sales and marketing leadership on territory design, quota planning, and commission models, translating requirements into system configurations

• Evaluate, implement, and integrate RevOps tooling (e.g., enrichment providers, sales engagement platforms, billing systems) via APIs and middleware like Workato or Zapier

• Audit and improve data quality, documenting definitions and building processes that keep pipeline reporting trustworthy

• Deliver weekly and monthly revenue reporting to leadership, surfacing risks and anomalies with clear recommendations

What We Are Looking For

• 3-6 years of revenue operations, sales operations, or business analyst experience, ideally in B2B SaaS

• Advanced SQL skills and hands-on experience with Salesforce administration (reports, flows, custom objects)

• Proficiency building dashboards in Looker, Tableau, or Power BI; comfort going from raw data to exec-ready narrative

• Experience with marketing automation and GTM integrations (HubSpot, Outreach, Gong, ZoomInfo, or similar)

• Strong process-design instincts: able to spot broken handoffs and fix them with tooling, automation, or documentation

• Bachelor's degree in a quantitative field, business, or equivalent practical experience

• Bonus: experience with Python or dbt for data modeling, CPQ/billing systems, and compensation-plan design