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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** Axel Springer SE - **Location:** Berlin, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Amazon Web Services, Microsoft Azure, Cloud Computing, Code Review, Python (Programming Language), Data Processing, Backend, Information Technology - **Published:** July 22, 2026 - **Apply:** https://career.axelspringer.com/de/job/senior-data-engineer-4 ## About the Role * a degree in computer science, engineering, or a related field; equivalent expertise proven through experience and impact is equally valued * senior-level experience delivering and operating data products or backend systems end-to-end in a cloud environment such as AWS, GCP, or Azure * deep, tool-independent grounding in data modeling, schema evolution, incremental and idempotent processing, late and dirty data handling, and the ability to explain why a pipeline is shaped the way it is, not just that it runs * strong Python skills with the discipline to write clean, well-tested, maintainable code - bring solid software-engineering practice to data work and pick up Go or other tools as needed * proven data-trust instincts, having applied quality checks, lineage, and freshness to keep real data products reliable for actual consumers * sound judgment on tools and trade-offs, with the ability to defend your choices, the options you ruled out, and what you would do differently * effective communication with non-engineers, a genuine ownership mindset, and experience mentoring data engineers across different seniority levels ## Description Was du bei uns bewegst: * own data products end-to-end, from building pipelines to responding to incidents and improving reliability * hands-on engineering: building, testing, and reasoning about the data transforms and services that run the business * build data-quality checks, lineage, and freshness directly into the work so data consumers can rely on it * design schemas that handle late and messy data and reflect how the business actually asks questions * collaborate with analysts, data scientists, and product managers to define data models contracts, and interfaces that deliver reliable, high-quality data * mentor mid-level and junior data engineers through code review, design feedback, and shared standards * tune transforms and pipelines for reliability and efficiency, and reduce operational toil over time Was du mitbringst: * a degree in computer science, engineering, or a related field; equivalent expertise proven through experience and impact is equally valued * senior-level experience delivering and operating data products or backend systems end-to-end in a cloud environment such as AWS, GCP, or Azure * deep, tool-independent grounding in data modeling, schema evolution, incremental and idempotent processing, late and dirty data handling, and the ability to explain why a pipeline is shaped the way it is, not just that it runs * strong Python skills with the discipline to write clean, well-tested, maintainable code - bring solid software-engineering practice to data work and pick up Go or other tools as needed * proven data-trust instincts, having applied quality checks, lineage, and freshness to keep real data products reliable for actual consumers * sound judgment on tools and trade-offs, with the ability to defend your choices, the options you ruled out, and what you would do differently * effective communication with non-engineers, a genuine ownership mindset, and experience mentoring data engineers across different seniority levels ## 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) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Are Code Reviews Worth It? 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