* Do you want to help shape modern data and AI infrastructures and make large datasets efficiently usable? As a Data Engineer, you will play a central role in building, integrating, and processing the data streams that drive our AI applications and models. You will work closely with our AI developers and the DevOps team, designing comprehensive data pipelines that connect the systems in our Kubernetes infrastructure.
YOUR TASKS
* You develop and operate fault-tolerant data pipelines (ETL/ELT) that reliably collect, process and provide large amounts of data.
* You will integrate external data sources, interfaces and services into our AI stack and ensure smooth data flows between applications, models and infrastructure.
* You will 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 appropriate tools and processes.
* You will work in an agile project environment with a dedicated team.
YOUR PROFILE
* You have a completed degree in computer science, data science, electrical engineering or a comparable qualification.
* You already have 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 have experience with containerization and Kubernetes, ideally in an on-premises environment.
* You have knowledge in the field of MLOps, for example in MLflow, Kubeflow or similar frameworks.
* Ideally, you would already have programming skills in Python and experience with DevOps processes.
* You enjoy working in a team, actively contribute, and play a key role in shaping current and future topics in the field of AI.