About the role Own the revenue engine end-to-end, from the data and code that generate a qualified pipeline at the top of the funnel, to the systems, automation, and analytics that turn that pipeline into predictable, efficient revenue. You combine hands-on engineering (Python, SQL, scraping/data pipelines) with CRM architecture and revenue analytics (HubSpot, cohort tracking, CAC/LTV/NRR) to build, ship, measure and optimize the full GTM engine across our four markets.
This role goes beyond project coordination or reporting. It focuses on designing and maintaining the data pipelines that support Sales, helping shape and optimize the CRM that powers the commercial funnel, and building the reporting and insights that enable the business to identify opportunities, improve processes, and drive revenue performance.
Your missions Lead Generation Engine & Data Acquisition Own and improve the Lead Generation codebase — write clean, tested, deployable Python and refactor it so it stays simple and fast as volume grows.
Collect and aggregate prospecting data through scraping,



scripting and data purchase; build pipelines that feed Sales a steady, reliable stream of qualified prospects.
Ensure prospecting data is accurate, available, secure and actionable across all markets.
Implement and evolve lead-scoring rules based on downstream revenue quality, not just close rates, so SDRs and AEs always work the highest-probability prospects first.
Revenue Performance Framework & Analytics Define and maintain the company-wide revenue performance scorecard: CAC, Payback, NRR, LTV/CAC, conversion by segment, ACV mix.
Build cohort-based performance tracking to monitor retention across 3-, 6- and 12-month periods by segment.
Monitor revenue leakage and identify systemic inefficiencies across the full funnel — from lead generation through onboarding, Sales and Customer Success.
Partner with Finance and Data teams to ensure accuracy, consistency and actionability of revenue intelligence.
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📌 Revenue Operations Engineer (Madrid)
🏢 Amenitiz
📍 Madrid