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

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