We are looking for aMid-Level Data Engineerto join ourRevenue Operationsteam, responsible for building, scaling, and maintaining data pipelines that support strategic revenue decisions.This role plays a key part in connecting data acrossMarketing, Sales, Customer Success, and Finance, ensuring high data quality, reliability, and availability.The position requireson-site presence in Madrid, with close collaboration across cross‑functional teams in a fast‑paced and constantly evolving environment.ResponsibilitiesData Engineering (Core)Design, build, and maintain scalable and reliable data pipelines (ETL/ELT).Develop and optimize analytical data models (bronze, silver, and gold layers).Ensure data quality, governance, and consistency.Monitor pipelines, proactively identify bottlenecks, and resolve failures.Work with large volumes of structured and semi‑structured data.Revenue OperationsIntegrate data from multiple sources, including:CRM systems (e.G., Hub Spot)Marketing platformsFinancial and billing systems (SAP)Product data sourcesBuild datasets to support analysis of:Sales funnel and pipelineRevenue forecastingRecurring revenue (MRR, ARR)Churn, retention, and expansionPerformance metrics for SDRs, AEs, and CSMsSupport the development of strategic KPIs and metrics for leadership and C‑level stakeholders.Partner closely with data analysts, Rev Ops,



and business teams.Technology & ToolsUse Databricks for data processing, transformation, and orchestration.Work extensively with advanced SQL and Python.Leverage the Google ecosystem, including:Big QueryGoogle Cloud StorageGoogle Sheets (automation and integrations)Enable BI tools and dashboards (e.G., Looker, Power BI, Tableau).Collaboration & EnvironmentCollaborate closely with business teams, translating requirements into technical solutions.Participate actively in agile ceremonies (planning, daily stand‑ups, reviews).Thrive in a dynamic, high‑growth, and fast‑changing ntinuously propose improvements in architecture, processes, and performance.RequirementsProven experience as a Mid‑Level Data Engineer.Strong expertise in SQL (data modeling and performance optimization).Solid experience with Python for data engineering.Hands‑on experience with Databricks.Experience with Google Cloud Platform (Big Query, GCS).Previous experience in Revenue Operations, Sales, or Finance.Knowledge of Saa S metrics (MRR, ARR, LTV, CAC, churn).Strong understanding of:ETL / ELT processesData Warehousing and Data LakesDimensional data modelingExperience with version control systems (Git).Nice to HaveExperience with BI tools.International work experience.Fluence in Spanish.Advanced English it's good.

📌 Data Engineer Revenue Operations (Madrid)
🏢 Blip
📍 Madrid