Data Engineer (m/f/d)

ANGEHEUERT GmbH · Frankfurt am Main · On-site

• Employment typeFull-time
• Experience levelMid level
• Salary signalSalary not listed
• Last checkedJust now
• Source valid throughNov 29, 2026

Role Overview

Data Engineer Are you technically skilled, enjoy exploring new approaches, and want to avoid being held back by existing structures and processes? As a Data Engineer , you will join an environment where many things are being built from the ground up and where you can actively contribute your own technical ideas. From architecture and data pipelines to data quality and AI interfaces, you will have the opportunity to develop modern solutions while taking ownership of their implementation. Apply now and take advantage of the technical freedom this position offers. Your benefits as Data Engineer Compensation: Enjoy an attractive salary with an additional variable component that reflects your experience and technical expertise. Creative Freedom: Help build a central data platform from the ground up and bring your own technical ideas to the table. You will have plenty of room to explore modern solutions and actively shape the technical architecture. Flexibility: Organize your working day largely on your own and work flexibly from home or anywhere in Germany. At the same time, you should be willing to attend important meetings, workshops, and in person collaboration when required. Workation: Take up to four weeks of workation within the EU and, subject to agreement, potentially beyond the EU. Pension: Benefit from an occupational pension scheme with a 50% employer contribution. Development: Take advantage of individual training opportunities, language courses, and personal learning programs. International Environment: Work in an international environment where both German and English are used as business languages. Your tasks as Data Engineer Data Layer: Take ownership of operating and further developing the Databricks based data platform, including workspaces, jobs, and permissions. Data Pipelines: Develop robust ETL and ELT pipelines for banking, treasury, payments, export finance, and other data sources. Architecture: Design Data Lake and Lakehouse structures as well as scalable and high performance data models. Data Quality: Implement automated quality checks and ensure data completeness, timeliness, and consistency. Monitoring: Build monitoring and alerting for pipelines, jobs, latency, 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 teams with data analysis and work closely with Architecture, Platform, Risk, and Compliance. Your profile Education: A degree in Computer Science, Data Engineering, Business Informatics, or a comparable qualification provides the foundation for this role. Experience: Several years of experience in Data Engineering and 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 modelling, 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: Strong communication skills and very good English at C1 level. Additional Skills: Experience with banking, finance, Power BI, DORA, SFTP, or AI and ML data pipelines is an advantage. Do you have your own ideas about how a modern data platform should be built and want the freedom to put them into practice? Then this role offers the technical freedom you rarely find within established structures. Find Jobs in Germany on Arbeitnow

Why It Matches

This full-time role is listed as on-site in Frankfurt am Main. The source does not expose a salary range, so confirm compensation before investing in a long application. The match score reflects role clarity, work mode, location, freshness, salary visibility, and description depth—not a promise that the employer will select a candidate.

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