• Own the GTM data models and pipelines that power analysis - building and maintaining them, setting high quality standards, and creating a safe and consistent semantic layer GTM can build on.
• Run deep-dive analyses on what's driving (and blocking) revenue: funnel conversion, segment performance, customer success, and rep productivity.
• Optimize the forecasting, quota, and capacity models leadership plans against, and pressure-test the assumptions behind them.
• Define how GTM interacts with data in an AI-first way—what's self-serve via Cursor and what's prebuilt into governed dashboards and applications.
• Partner with the product Data and Enterprise Engineering teams to ensure GTM has the data it needs and uses consistent pipelines, definitions, and models wherever possible.
Requirements
Your SQL is exceptional (non-negotiable), and you're fluent working across large, complex datasets.
You've built and maintained production data pipelines and models, and you pick up unfamiliar data structures quickly—CRM and GTM systems included.
You've built forecasting, quota, or capacity models, and you're a strong modeler in both code and spreadsheets.
You can operationalize metrics and tooling for non-technical stakeholders so they can self-serve.
You have strong analytical judgment and can move between the big picture and the details—from "how should we measure GTM health?" to "why is this one segment's conversion off?"
Direct experience with GTM, revenue, or sales analytics is preferred, but a strong analytics or data-science background and the drive to go deep on the GTM domain matter more.
You operate with high ownership, are comfortable pushing back on senior leaders, and bias toward durable systems over one-off decks.
Core Competencies
Expertise in building and maintaining GTM data models and pipelines, with a strong focus on SQL, forecasting, and capacity modeling. Ability to operationalize metrics for non-technical stakeholders and conduct deep-dive analyses to drive revenue insights.
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