ppWe are looking for a bMid-Level Data Engineer /b to join our bRevenue Operations /b team, responsible for building, scaling, and maintaining data pipelines that support strategic revenue decisions. /p pThis role plays a key part in connecting data across bMarketing, Sales, Customer Success, and Finance /b, ensuring high data quality, reliability, and availability. /p pThe position requires bon-site presence in Madrid /b, with close collaboration across cross‑functional teams in a fast‑paced and constantly evolving environment. /p h3Responsibilities /h3 ul liData Engineering (Core) /li liDesign, build, and maintain scalable and reliable data pipelines (ETL/ELT). /li liDevelop and optimize analytical data models (bronze, silver, and gold layers). /li liEnsure data quality, governance, and consistency. /li liMonitor pipelines, proactively identify bottlenecks, and resolve failures. /li liWork with large volumes of structured and semi‑structured data. /li liRevenue Operations /li liIntegrate data from multiple sources, including: ul liCRM systems (e.g., HubSpot) /li liMarketing platforms /li liFinancial and billing systems (SAP) /li liProduct data sources /li /ul /li liBuild datasets to support analysis of: ul liSales funnel and pipeline /li liRevenue forecasting /li liRecurring revenue (MRR, ARR) /li liChurn, retention, and expansion /li liPerformance metrics for SDRs, AEs, and CSMs /li /ul /li liSupport the development of strategic KPIs and metrics for leadership and C‑level stakeholders. /li liPartner closely with data analysts, RevOps, and business teams.



/li liTechnology Tools /li liUse Databricks for data processing, transformation, and orchestration. /li liWork extensively with advanced SQL and Python. /li liLeverage the Google ecosystem, including: ul liBigQuery /li liGoogle Cloud Storage /li liGoogle Sheets (automation and integrations) /li /ul /li liEnable BI tools and dashboards (e.g., Looker, Power BI, Tableau). /li liCollaboration Environment /li liCollaborate closely with business teams, translating requirements into technical solutions. /li liParticipate actively in agile ceremonies (planning, daily stand‑ups, reviews). /li liThrive in a dynamic, high‑growth, and fast‑changing environment. /li liContinuously propose improvements in architecture, processes, and performance. /li /ul h3Requirements /h3 ul liProven experience as a Mid‑Level Data Engineer. /li liStrong expertise in SQL (data modeling and performance optimization). /li liSolid experience with Python for data engineering. /li liHands‑on experience with Databricks. /li liExperience with Google Cloud Platform (BigQuery, GCS). /li liPrevious experience in Revenue Operations, Sales, or Finance. /li liKnowledge of SaaS metrics (MRR, ARR, LTV, CAC, churn). /li liStrong understanding of: ul liETL / ELT processes /li liData Warehousing and Data Lakes /li liDimensional data modeling /li /ul /li liExperience with version control systems (Git). /li /ul h3Nice to Have /h3 ul liExperience with BI tools. /li liInternational work experience. /li liFluence in Spanish. /li liAdvanced English it's good. /li /ul /p #J-18808-Ljbffr

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