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 streamingevaluating 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 contextcontribute to ensuring continuous quality, reusability and performance improvement and take responsibility for applications and stakeholders during development, commissioning and operationautomating and deploying data transformations and pipelines on the provided Data Platformworking in an accurate (clean-code) and test-driven software development environment with a devops mindsetin 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 engineeringSetup, configuration and automated deployment of Infrastructure Artifacts, with tools like Jenkins, Puppet or TerrraformConfiguration and deployment of CI/CD Pipelines using Git or similar toolsExperience with Cloud technologies like Microsoft Azure or similar environmentStrong knowledge of of serverless (Azure Data Factory, Synapse Analytics) or container based (Kubernetes) application provisioning and deploymentStrong experience in setup of network configuration, service communication and integration patterns (JDBC/ODBC, OData, Rest APIs)Monitoring and logging (preferably Elastic, Datadog), telemetry systemsDeep understanding of resource management and optimization (CPU, RAM, Disk)Agile software development using Scrum / Kanban