Senior Data Engineer

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

• 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

Axel Springer is Europe’s leading digital publisher and a global media and technology company headquartered in Berlin. With renowned brands such as BILD, POLITICO Germany, WELT und BUSINESS INSIDER Germany, we reach millions of users worldwide. We combine the reach of an established industry leader with the agility of a startup, constantly driving innovation to transform journalism for the digital age.

Our corporate strategy places AI at the center: “Digital is the new print. AI is the new digital.” This vision reflects our belief that the fusion of artificial intelligence and human creativity will shape the future of media. Our National Media & Tech division is the central tech hub that ensures our journalism is supported by state-of-the-art technology, positioning our brands to thrive in the digital age. We believe in the future of journalism as a business model and invest in forward-looking technologies. Our five essentials are the values that unite us and guide us in our commitment to freedom.

You’ll join the data engineering team at the heart of Axel Springer’s media and advertising business. Your daily work is fundamentally hands-on. You write the transforms, pipelines, and data models that keep reliable, well-structured data flowing to the product teams, analysts, and data scientists who build on it. You’ll work within the Data Engineering discipline, reporting to a Data Engineering Manager and embedded day-to-day in one of our business domains alongside software engineers, data scientists, analysts, and product partners. Typical domains include subscriptions, advertising, audience tracking, content performance, and event data. The stack is Python-first and cloud-native, with parts in Go. Data engineering depth is what makes this work possible.