Data Engineer (m/w/d)

• You want to shape modern data and AI infrastructure and make large data volumes usable efficiently? As a Data Engineer, you play a central role in building, integrating, and processing data streams that drive our AI applications and models. You work closely with our AI developers and the DevOps team together and design comprehensive data pipelines that enable us to connect systems in our Kubernetes infrastructure.

YOUR TASKS

• You develop and operate fault-tolerant data pipelines (ETL/ELT) that collect, process, and provide large data volumes reliably.
• You integrate external data sources, interfaces, and services into our AI stack and ensure smooth data flows between applications, models, and infrastructure.
• You support the setup and operation of MLOps pipelines, for example, for model training, evaluation, and deployment.
• You develop and maintain data models, data structures, and storage concepts for SQL-, NoSQL- and object-storage systems.
• You ensure that data quality, monitoring, and observability are guaranteed through suitable tools and processes.
• You work in an agile project environment with a motivated team.

YOUR PROFILE

• You bring a completed degree in the field of Computer Science, Data Science, Electrical Engineering, or a comparable qualification.
• You have already gained experience in data engineering and are familiar with common tools such as Airflow, Kafka, or Spark.
• You have experience with databases and data modeling (SQL, NoSQL, Object Storage).
• You bring experience with containerization and Kubernetes, ideally in an on-premises environment.
• You possess knowledge of MLOps, for example, in MLflow, Kubeflow, or comparable frameworks.
• It would be optimal if you already brought programming knowledge in Python and experience with DevOps processes.
• You work well in a team, actively participate, and shape current and future topics in the AI field significantly.

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