We are looking for a Mid-Level Data Engineer to join our Revenue Operations team, responsible for building, scaling, and maintaining data pipelines that support strategic revenue decisions.

This role plays a key part in connecting data across Marketing, Sales, Customer Success, and Finance, ensuring high data quality, reliability, and availability.

The position requires on-site presence in Madrid, with close collaboration across cross‑functional teams in a fast‑paced and constantly evolving environment.

Responsibilities

- Data 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 Operations
- Integrate data from multiple sources, including:
- CRM systems (e.g., HubSpot)
- Marketing platforms
- Financial and billing systems (SAP)
- Product data sources

- Build datasets to support analysis of:

- Sales funnel and pipeline
- Revenue forecasting
- Recurring revenue (MRR, ARR)
- Churn, retention, and expansion
- Performance metrics for SDRs, AEs, and CSMs

- Support the development of strategic KPIs and metrics for leadership and C‑level stakeholders.
- Partner closely with data analysts, RevOps, and business teams.
- Technology & Tools




- Use Databricks for data processing, transformation, and orchestration.
- Work extensively with advanced SQL and Python.
- Leverage the Google ecosystem, including:

- BigQuery
- Google Cloud Storage
- Google Sheets (automation and integrations)

- Enable BI tools and dashboards (e.g., Looker, Power BI, Tableau).
- Collaboration & Environment
- Collaborate 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 environment.
- Continuously propose improvements in architecture, processes, and performance.

Requirements

- Proven 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 (BigQuery, GCS).
- Previous experience in Revenue Operations, Sales, or Finance.
- Knowledge of SaaS metrics (MRR, ARR, LTV, CAC, churn).
- Strong understanding of:
- ETL / ELT processes
- Data Warehousing and Data Lakes
- Dimensional data modeling

- Experience with version control systems (Git).

Nice to Have

- Experience with BI tools.
- International work experience.
- Fluence in Spanish.
- Advanced English it's good.

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