Help us reshape how Finance works at Axpo. As a core member of our Finance Digital & Data team, you'll connect data engineering, automation and dashboards into practical solutions that make Finance processes faster and more reliable.
What you will do:
Build and operate data pipelines on Databricks using Python (PySpark) and SQL
Design curated, business-ready datasets and reusable data products for Finance reporting and automation
Develop workflows with Power Automate that connect Databricks, SQL databases, ERP systems and Microsoft services
Create and maintain dashboards and reporting solutions that support operational decision-making
Support colleagues in Finance in building and maintaining their own front-end solutions, such as Power BI reports and apps
Contribute backend components and integrations that connect Finance applications, data products and user-facing tools
What you bring & who you are:
Experience in data engineering, software engineering, business intelligence or a related technical role
Practical experience with Python and PySpark-based data pipelines,



plus good knowledge of SQL and data modelling
Hands-on experience with Databricks or a comparable modern data platform
Experience building dashboards or reporting solutions – ideally with Power BI
You have experience with workflow or process automation, ideally using Microsoft Power Automate
Strong communicator who enjoys explaining technical topics to non-technical stakeholders; even if you don't meet every point above, we look forward to your application
About the team:
We're a small, close-knit Finance Digital & Data team bridging Finance and technology. We value curiosity, pragmatic solutions and knowledge sharing, and we welcome perspectives from all backgrounds and career paths.
Benefits:
At our company, we strive to create a culture of continuous learning, personal growth, and inter- national community involvement. We're passionate about providing our employees with the tools and resources they

📌 Finance Data Engineer (Madrid)
🏢 Axpo Group
📍 Madrid