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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Jedox AG - **Location:** Freiburg im Breisgau, Germany (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Microsoft Windows, Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Data as a Services, Data Architecture, Data Cleansing, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Python (Programming Language), Meta-Data Management, Metadata Standards, SQL Azure, Salesforce.Com, Search Technologies, Microsoft SharePoint, SQL Databases, Data Streaming, Systems Integration, Unstructured Data, Enterprise Data Management, Enterprise Software Applications, Azure Data Factory, Office365, Apache Spark, Data Layers, Microsoft Fabric, Jedox, Data Lakes, Data Lineage, Data Management, Restful APIs, Data Pipelines - **Published:** July 8, 2026 - **Apply:** https://de.indeed.com/viewjob?jk=ca899d50fb6a2e11 ## About the Role * 7+ years in data engineering, including 3+ years building enterprise-scale cloud platforms, with proven greenfield architecture and AI/ML data preparation experience. * Expertise in Python and SQL, and I have hands-on experience with Spark, Microsoft Fabric, the Azure Data Platform and Delta Lake. I am also experienced in ETL/ELT, data modelling and warehousing. * Experience integrating enterprise systems (e.g., Salesforce, SharePoint, M365, Azure SQL/Data Lake) and working with REST APIs and modern data architectures. * Solid understanding of metadata management, master data management, and semantic modelling. * Certifications in Azure/Fabric and experience with Purview, Synapse, Data Mesh, graph/vector databases, Azure AI Search, or event streaming. * Growth-oriented, proactive and driven by innovation, execution excellence and building impactful, scalable data solutions. * Excellent English communication skills are required ## Description As a Data engineer, you will be responsible for designing, developing and operating our enterprise data platform. Your role will involve ensuring that data is integrated, governed and AI-ready, thereby creating the backbone for all intelligent applications and insights across the business. * Design and own the enterprise data platform: Build a scalable Microsoft Fabric data infrastructure using a medallion lakehouse architecture (Bronze, Silver or Gold) with Delta Lake. * Develop and operate data pipelines: Create robust batch and streaming ETL/ELT pipelines with schema evolution, automated transformation and strong data quality validation. * Integrate enterprise systems: Connect to data sources such as SharePoint, Salesforce, Microsoft 365, Azure SQL, ERP/CRM systems, file repositories and REST APIs. * Ensure performance and reliability: Optimize storage and processing across structured and unstructured data, including monitoring, alerting, and operational stability. * Build semantic data layers & governance: Establish a taxonomy and metadata standards, as well as semantic models and data cataloguing and lineage tracking. Enforce access control, compliance and security. * Drive AI readiness: Prepare data for AI use cases through document chunking, embedding pipelines, and vector-ready datasets for RAG. * Expose knowledge services & collaborate: Develop reusable APIs and data services for AI applications and work cross-functionally with AI, analytics, and business teams (#OneTeam)., As a tech-driven company, Jedox uses modern technologies - including AI - to continuously improve our processes. In recruiting, AI may support us in screening and structuring applications. It does not replace human judgment, but helps us reduce bias and ensure a consistent candidate experience. Your application is always reviewed by real people. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Hacking MSSQL on Cloud. All of them. 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