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

1. 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.

2. 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.

3.



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).

4. 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.

📌 Data Engineer Revenue Operations (Madrid)
🏢 Empresa líder
📍 Madrid