Data Engineer (m/f/d)

Are you technically adept, do you enjoy trying out new approaches, and don't want to be held back by existing structures in every decision? As a Data Engineer, you can expect an environment where many things are being rebuilt and you can actively contribute your technical ideas. From architecture and data pipelines to data quality and AI interfaces, you can develop modern solutions and take responsibility for their implementation. Apply now and leverage the technical freedom this position offers. 

Your Benefits as a Data Engineer

• Compensation: Look forward to an attractive salary with an additional variable component that matches your experience and technical expertise.  

• Scope for Design: Help build a central data platform from scratch and bring in your own technical ideas. There is plenty of room here to try out modern solutions and actively shape the technical architecture. 

• Flexibility: Largely design your workday yourself and work flexibly from home or from your place of residence in Germany. At the same time, your willingness to participate on-site is expected for important meetings, workshops, and personal exchange. 

• Workation: Utilize up to four weeks of workation within the EU and, if applicable, beyond by arrangement. 

• Retirement Provision: Benefit from a company pension plan with 50% employer contribution. 

• Development: Utilize individual further training, language courses, and personal learning opportunities. 

• Internationality: Work in an international environment with German and English as business languages. 

Your Responsibilities as a Data Engineer

• Data Layer: Take over the operation and further development of the Databricks-based data platform, including workspaces, jobs, and permissions. 

• Data Pipelines: Develop robust ETL and ELT pipelines for banking, treasury, payments, export financing, and other data sources. 

• Architecture: Design Data Lake and Lakehouse structures as well as scalable and performant data models. 

• Data Quality: Implement automated quality checks and ensure the completeness, timeliness, and consistency of the data. 

• Monitoring: Build monitoring and alerting for pipelines, jobs, latencies, and errors. 

• Governance: Document data flows and lineage, and support data classification, access controls, and regulatory requirements. 

• AI Enablement: Provide suitable data and interfaces for AI use cases and MLOps. 

• Collaboration: Support business units with data analysis and work closely with Architecture, Platform, Risk, and Compliance. 

Your Profile as a Data Engineer

• Education: A degree in Computer Science, Data Engineering, Business Informatics, or a comparable qualification forms the basis. 

• Experience: Several years of experience in data engineering and in building productive data platforms. 

• Technology: Very good knowledge of Databricks, SQL, and modern ETL and ELT patterns. 

• Architecture: Experience with Data Lake or Lakehouse architectures, data modeling, and data quality. 

• Cloud: Experience with Infrastructure as Code in cloud environments is important, ideally complemented by Azure or AWS knowledge. 

• Operations: Experience with monitoring, error handling, and operationalizing productive data pipelines. 

• Communication: Good communication skills and very good English skills at C1 level. 

• Plus Points: Experience with banking, finance, Power BI, DORA, SFTP, or AI and ML data pipelines. 

Do you have your own ideas about how a modern data platform should be structured and want to be able to implement them? Then the technical scope for design that you will search for in vain in many established structures awaits you here. 

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