Your role building highly scalable data products for the automated consolidation, process and analyse large amounts of data for machine learning - from conception to prototyping to operation, batch and streaming evaluating the latest trends and technologies, help shaping our architecture decisions including DevOps / DataOps processes and drive innovative solutions for data management in the machine learning context contribute to ensuring continuous quality, reusability and performance improvement and take responsibility for applications and stakeholders during development, commissioning and operation automating and deploying data transformations and pipelines on the provided Data Platform working in an accurate (clean-code) and test-driven software development environment with a devops mindset in close cooperation with data scientists, you implement exciting AI use cases (e.g. entity extraction, recommender, chatbots) with data of all kinds (e.g. time series, images, documents) Your profile At least 3 years of relevant professional experience as a DevOps engineer with strong inclination to data engineering Setup, configuration and automated deployment of Infrastructure Artifacts, with tools like Jenkins, Puppet or Terrraform Configuration and deployment of CI/CD Pipelines using Git or similar tools Experience with Cloud technologies like Microsoft Azure or similar environment Strong knowledge of of serverless (Azure Data Factory, Synapse Analytics) or container based (Kubernetes) application provisioning and deployment Strong experience in setup of network configuration, service communication and integration patterns (JDBC/ODBC, OData, Rest APIs) Monitoring and logging (preferably Elastic, Datadog), telemetry systems Deep understanding of resource management and optimization (CPU, RAM, Disk) Agile software development using Scrum / Kanban