Senior Revenue Operations Manager

What You’ll Do

• First 90 days: Build core dashboards, identify process/data gaps, establish remediation plans.
• First 180 days: Create capacity and territory models, map the full tech stack and integrations, define the attribution model.
• First 12 months: Achieve predictable forecasting (within ±10%) and establish a scalable enablement foundation.

Day to day, Week to week, Month to month

Systems & Data Foundation

• Own vendor relationships, tools, and integrations (Salesforce, Gong, ChiliPiper, etc.).
• Establish data quality standards, access controls, and governance practices.
• Build durable dashboards and ad hoc reporting that clearly answer “where are we vs. target?”
• Perform ongoing process and data gap analysis, prioritizing practical improvements while keeping long-term scalability in mind.
• Evaluate and implement technology or process improvements to support revenue growth.

CS & Sales Enablement

• Operationalize CS function: customer health, churn prediction, renewal workflows, escalation paths, expansion playbooks.
• Create rules of engagement between Sales and CS for complex GTM.
• Build enablement function infrastructure (topics/process/schedule—not training delivery).

Strategic Revenue Support

• Build tracking for strategic/payment partner merchants critical to NRR.
• Analyze performance trends to guide strategy: win/loss, deal cycle length, seasonality, retention, segmentation bands, and customer bands.
• Create capacity planning models based on pipeline velocity and customer growth.
• Territory planning, quota setting, and compensation administration.
• Support pricing and packaging changes with data and tracking.
• Support mid-funnel pipeline reviews and Sales/CS QBRs.
• Identify and surface GTM and CS inefficiencies through data analysis.
• Build merchant health scoring, expansion potential tracking, and red-to-green workflows.
• Design reporting that gives executives visibility, managers clarity, and reps actionable insights—from pipeline health to forecasting accuracy.

You Might Be a Fit If

• You’ve built RevOps from scratch (6–8+ years of experience, including at least one 0→1 build or major foundation reset).
• You’re deeply data-driven, with a mindset of “if the data isn’t there, how do we get it?”
• You’re comfortable speaking truth to power, using data to surface trade-offs and inform decisions, even when conversations are uncomfortable.
• AI is a strength, not a buzzword—you can point to concrete examples of how you use it in your current role.
• You’re hands-on te