Analyzes and improves revenue pipeline data, forecasting, CRM quality, and go-to-market performance across Sales, Marketing, Customer Success, and Finance. The role requires 3–5 years of RevOps or comparable analytical GTM experience, advanced spreadsheet skills, and basic SQL and BI capabilities.
Salary not listed
Hybrid5+ YOERevenue Operations
About the role
Responsibilities
Own CRM data integrity in HubSpot by monitoring data flows, optimizing automations, enforcing hygiene standards, and maintaining trustworthy pipeline inputs.
Build and maintain dashboards and reporting for weekly revenue reviews, including pipeline coverage, stage flow, conversion, deal age, and win rates.
Support forecasting through bottom-up analysis, pipeline inspection, and clear identification of risks such as slipped deals, sandbagging, and ghost pipeline.
Analyze large datasets with SQL and business intelligence tools to identify trends and drivers for go-to-market decisions.
Measure the impact of outbound, account-based marketing, partner, and marketing motions to guide spending and targeting.
Partner with Sales, Marketing, Customer Success, and Finance, translating complex analysis into clear narratives for executive and non-technical audiences.
Use AI and automation to improve reporting, data quality, and analysis.
Requirements
Experience owning CRM data quality or revenue reporting end-to-end, with demonstrated improvements in hygiene or accuracy.
Ability to turn ambiguous business questions into clear analysis and recommendations.
Strong written and verbal communication skills, including comfort presenting findings to executives.
Advanced spreadsheet skills, basic SQL and BI capabilities, and some familiarity with Python for analysis or automation.
Familiarity with CRM and marketing automation systems; HubSpot experience is strongly preferred.
Ability to manage multiple projects and keep cross-functional partners on track.
3–5 years of experience in Revenue Operations, Sales Operations, or a comparable analytical go-to-market role, ideally in B2B SaaS.
Nice-to-haves
Hands-on use of AI in a revenue technology stack.
Exposure to attribution, cohort and lifetime-value analysis, or commission analytics.
Compensation and Benefits
Competitive pay.
Equity with significant upside.
Flexible schedules and time off.
Benefits designed to support healthy, well-balanced employees.
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