Senior Manager, Revenue Operations & Analytics
VGS · United States · 1 mo ago
RemoteRemoteManagementFull-time
What you will be doing at VGS (Responsibilities)
- Revenue Intelligence & Reporting (The "What")
- Own and maintain the tracking of company, client, and product metrics and KPIs.
- Leverage AI to build out business and client performance and insights from the VGS data.
- Run daily billable usage analysis to proactively flag revenue anomalies before they become billing disputes.
- Translate complex data sets into actionable narratives for the leadership team.
- Data & Systems Architecture (The "How")
- Partner with our Data Engineers to manage and optimize the flow of data through Fivetran, Salesforce, and Sigma.
- Act as the bridge to Engineering: Translate business requirements into technical specs and navigate data backfills or pipeline failures without losing context.
- Directly manage Salesforce hygiene and the implementation of outbound/growth tools like Clay.ai.
- Commercial Forensic Operations (The "Why")
- Investigate the "weeds": Troubleshoot and investigate line item analysis to resolve client issues or provide additional insights.
- Own the billing feedback loop: Flag overages, advise Account Managers on contested invoices, and ensure our billing logic matches our legal commitments.
What we are looking for from you (Requirements)
- 5+ years in RevOps, Sales Ops, or Data Analytics
- Expert Level: Salesforce (Admin preferred) and Sigma (or similar BI like Looker/Tableau).
- Experience with Data pipelines is a massive plus. You are comfortable writing SQL and investigating data pipelines, even if you aren't a full-time dev.
- Experience with billing and usage based models
- You enjoy being the person who links Sales, Finance, and Engineering.
- You have the confidence to "hold the line" on a billing dispute because you’ve done the data legwork to prove your case.
- You believe a visualization is only as good as the SQL behind it. You look for context and "data smell" before hitting 'refresh'.
- Data Driven: You are curious, wanting to understand the underlying drivers to the data story.