Job Description

As a Data Platform Engineer with a focus on data engineering, you will be responsible for building and operating modern data platforms. You will develop scalable data pipelines and ETL/ELT processes on Microsoft Azure to make large amounts of data from different sources usable



You develop stable batch and streaming pipelines with Azure Data Factory/Databricks on Microsoft Azure. Best practices such as Delta Lake, automated workflows and VNet-Securing ensure reliability. You will take responsibility for sub-projects in data integration, e.g. setting up a data path from operational systems in a data lakehouse. You will implement and optimize ETL/ELT routes (with Azure Data Factory, Databricks/Spark etc.) and ensure data quality. Use Azure data services for storage and processing (Data Lake, Azure SQL, Databricks, MS Fabric) efficiently. Participates in setting up CI/CD pipelines (Azure DevOps or GitHub) for automated deployments and collaborates closely with Data Scientists and Analytics teams to provide data for analytics and ML

2-4 years of experience in data engineering or data platform development Solid knowledge of SQL and programming (Python or Scala) as well as experience with Azure Data Services (e.g. Azure Data Factory, Azure Databricks, Synapse) Familiarity with data modeling (e.g. Star Schema, Kimball) and data platform monitoring & performance optimization. Experience in dealing with version management (Git) and DevOps practices (Continuous Integration, Infrastructure as Code). Communication & Collaboration: Working with data scientists, analysts and clients and translating technical concepts for non-technical people Problem solving & analytical thinking: You optimize data streams, identify bottlenecks and find creative solutions * Language skills: German fluent, English good.