Data Engineer Revenue Operations

TL;DR

Mid-Level Data Engineer (Revenue Operations): Building and optimizing scalable and reliable data pipelines and analytical data models for strategic revenue decisions with an accent on data quality, governance, and consistency. Focus on integrating data from CRM, marketing, financial, and product systems and enabling analysis of sales funnel, revenue forecasting, and SaaS metrics.

Location: On-site in Madrid, Spain

Company

hirify.global is a company seeking a Mid-Level Data Engineer for its Revenue Operations team to build and maintain data pipelines supporting strategic revenue decisions.

What you will do

• Design, build, and maintain scalable and reliable ETL/ELT data pipelines.
• Develop and optimize analytical data models (bronze, silver, and gold layers).
• Ensure data quality, governance, and consistency for all revenue-related data.
• Integrate data from CRM, marketing, financial, and product data sources.
• Build datasets to support analysis of sales funnel, revenue forecasting, and key SaaS metrics.
• Partner closely with data analysts, RevOps, and business teams.

Requirements

• Proven experience as a Mid-Level Data Engineer.
• Strong expertise in SQL (data modeling and performance optimization) and Python for data engineering.
• Hands-on experience with Databricks and Google Cloud Platform (BigQuery, GCS).
• Previous experience in Revenue Operations, Sales, or Finance.
• Strong understanding of ETL/ELT processes, Data Warehousing, Data Lakes, and Dimensional Data Modeling.
• Experience with version control systems (Git).

Nice to have

• Experience with BI tools.
• International work experience.
• Fluence in Spanish.
• Advanced English proficiency.

Culture & Benefits

• Close collaboration across cross-functional teams in a fast-paced environment.
• Active participation in agile ceremonies (planning, daily stand-ups, reviews).
• Opportunity to thrive in a dynamic, high-growth, and fast-changing environment.
• Continuous proposal of improvements in architecture, processes, and performance.