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