Senior Software Engineer Data

Was du bei uns bewegst:

• build data products as production software by designing, implementing, testing, deploying, and operating end-to-end systems
• bring backend engineering rigor to data through clean code, sensible APIs, automated testing, and strong observability
• own systems end-to-end and stay responsible for incidents, operational quality, performance tuning, and continuous improvement
• make data trustworthy by building quality checks, lineage, freshness, and clear ownership from the start
• design schemas, data contracts and domain models that evolve safely, handle late data, and reflect real business questions
• partner with product, engineering, and data science to deliver reliable, high-quality data and lift standards through active mentoring of mid-level and junior engineers
• tune pipelines, services, and data models for reliability, performance, and cost-efficiency

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 backend systems, data products, APIs, services, or pipelines end-to-end in a cloud environment such as AWS, GCP, or Azure
• strong software engineering fundamentals with Python, writing clean, well-tested, maintainable code, and the ability to quickly pick up Go and other tools; experience with cloud data, lakehouse platforms, and high-throughput processing is a plus
• whether you come as a senior backend engineer moving into data or a data engineer with meaningful backend experience, you bring either solid depth in data modeling, schema evolution, incremental and idempotent processing, and late data handling, or strong transferable instincts and a genuine drive to go deeper
• sound judgment on APIs, data contracts, schemas, and ownership boundaries, including the ability to reason about compute cost and trade-offs, not just whether a system runs
• data-trust instincts: you treat quality checks, lineage, freshness, observability, and documentation as first-class deliverables and operate data products like real production systems
• strong collaboration and communication skills, including comfort working with non-engineers, valuing documentation and quality as glue work, and mentoring engineers at a range of levels
• you take responsibility for outcomes, partner with your team and stakeholders to align on direction, and drive work forward

• 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 backend systems, data products, APIs, services, or pipelines end-to-end in a cloud environment such as AWS, GCP, or Azure
• strong software engineering fundamentals with Python, writing clean, well-tested, maintainable code, and the ability to quickly pick up Go and other tools; experience with cloud data, lakehouse platforms, and high-throughput processing is a plus
• whether you come as a senior backend engineer moving into data or a data engineer with meaningful backend experience, you bring either solid depth in data modeling, schema evolution, incremental and idempotent processing, and late data handling, or strong transferable instincts and a genuine drive to go deeper
• sound judgment on APIs, data contracts, schemas, and ownership boundaries, including the ability to reason about compute cost and trade-offs, not just whether a system runs
• data-trust instincts: you treat quality checks, lineage, freshness, observability, and documentation as first-class deliverables and operate data products like real production systems
• strong collaboration and communication skills, including comfort working with non-engineers, valuing documentation and quality as glue work, and mentoring engineers at a range of levels
• you take responsibility for outcomes, partner with your team and stakeholders to align on direction, and drive work forward

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 be part of a team that builds the data products powering Axel Springer’s media and advertising business. That includes the pipelines, services, and modeled datasets that product teams, analysts, and data scientists rely on every day. You’ll work within the Data Engineering discipline, reporting to a Data Engineering Manager while being embedded day-to-day in one of our business domains. Typical domains include subscriptions, advertising, audience tracking, content performance, and event data, and you’ll work alongside software engineers, data scientists, analysts, and product partners. The stack is Python-first and cloud-native, with parts in Go. Strong engineering judgment matters more than familiarity with any specific platform.