Data Engineer

AI Service Partners (ASP) helps enterprise clients successfully implement and scale GenAI and data initiatives, from central data platforms to intelligent automation, working out of Munich and Berlin.

We work close to the client, solving real operational problems rather than building demos, and we're building a team that combines technical depth with a pragmatic, ownership-driven delivery mindset.

As Data Engineer at ASP, you'll build the technical backbone behind our clients' data and AI initiatives: designing pipelines, integrations, and data infrastructure that run in real corporate production environments, not sandboxes.

You'll work directly on high-stakes enterprise projects where your work is the foundation everything else, from reporting to automation to GenAI use cases, is built on.

Tasks Design, build, and operate data pipelines, integrations, and data infrastructure in real corporate production environments Build APIs and connectors to integrate heterogeneous systems and keep data mapped consistently across them Set up and manage cloud data infrastructure, including access rights, identity, and security configuration Work with modern data platform tools such as Microsoft Fabric, Databricks, or similar to build and operate scalable data solutions for clients Lay the technical foundation that everything else, from reporting to automation to GenAI use cases, is built on Requirements Experience designing, building, and operating data pipelines in a corporate production environment A solid understanding of data quality practices and how to map data consistently across systems Hands-on experience integrating heterogeneous systems, including building APIs and connectors Knowledge of one or more cloud providers (e.g., Microsoft Azure), including setting up access rights/IAM and security configuration Experience with modern data platform tools such as Microsoft Fabric, Databricks, or similar Good knowledge of networking and security fundamentals as they apply to data infrastructure A proven track record delivering this kind of work, ideally on real, high-stakes projects rather than internal or academic ones, is a big plus