Senior Manager, Revenue Operations & Analytics

What you will be doing at VGS (Responsibilities)...

1. Revenue Intelligence & Reporting (The "What")

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• Own and maintain the tracking of company, client, and product metrics and KPIs.
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• Leverage AI to build out business and client performance and insights from the VGS data.
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• Run daily billable usage analysis to proactively flag revenue anomalies before they become billing disputes.
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• Translate complex data sets into actionable narratives for the leadership team.

1. Data & Systems Architecture (The "How")

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• Partner with our Data Engineers to manage and optimize the flow of data through Fivetran, Salesforce, and Sigma .
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• Act as the bridge to Engineering: Translate business requirements into technical specs and navigate data backfills or pipeline failures without losing context.
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• Directly manage Salesforce hygiene and the implementation of outbound/growth tools like Clay.ai .

1. Commercial Forensic Operations (The "Why")

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• Investigate the "weeds": Troubleshoot and investigate line item analysis to resolve client issues or provide additional insights.
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• 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)...
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• 5+ years in RevOps, Sales Ops, or Data Analytics
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• Expert Level: Salesforce (Admin preferred) and Sigma (or similar BI like Looker/Tableau).
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• 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.
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• Experience with billing and usage based models
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• You enjoy being the person who links Sales, Finance, and Engineering.
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• You have the confidence to "hold the line" on a billing dispute because you’ve done the data legwork to prove your case.
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• You believe a visualization is only as good as the SQL behind it. You look for context and "data smell" before hitting 'refresh'.
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• Data Driven You are curious, wanting to understand the underlying drivers to the data story.