GEA Group is seeking a motivated, hands-on Data Engineer (f/m/d) to join our global data platform team within our Enterprise IT organization at our headquarters in Düsseldorf. In this role, you will play a key part in designing, building, and optimizing data pipelines that enable advanced analytics and data-driven decision-making across the organization.

We are at the beginning of a strategic journey to establish a decentralized data management operating model on our global data platform. This transformation is in its early stages, and we are looking for professionals who are eager to contribute, innovate, and help shape this journey. If you thrive in an environment where collaboration meets responsibility and where your ideas can drive meaningful change, this is your opportunity to make a real impact.

Your Tasks:

In this role, you will be responsible for designing, developing, and maintaining scalable data pipelines and ETL processes leveraging Azure Data Factory, Databricks (Lakeflow), and other modern technologies. You will create and optimize data models for both structured and unstructured data to enable impactful analytics and business use cases.

Collaboration is key - you will work closely with domain teams, such as Division, GEA Digital and other Corporate Function to implement Data Mesh principles and support a federated data management approach. By applying CI/CD pipelines and DataOps best practices, you will automate workflows and deployments to ensure efficiency and reliability.

A strong focus on data quality, security, and compliance across all data products and use cases is essential. You will partner with business stakeholders to understand requirements and deliver reliable, high-performance data solutions.

Finally, you will drive continuous improvement of our global data platform and analytics capabilities through innovation and the adoption of best practices.

• Degree in Computer Science, Data Engineering, Information Systems, or a related field.
• At least 3 years of professional experience in data engineering or a similar technical role.
• Strong hands-on experience with modern data platforms, particularly Databricks and Azure Data Factory, as well as solid proficiency in SQL and Python-based frameworks (e.g., DBT, Pandas).
• Proven experience with CI/CD pipelines, DataOps practices, and contemporary data engineering workflows.
• Ideally, experience with Data Mesh concepts and federated data management approaches.
• Experience working with cloud-based data platforms, preferably Microsoft Azure.
• An independent, proactive, and solution-oriented working style combined with strong teamwork skills.
• Excellent communication skills in English, .