Job
- Level
- Senior
- Job Field
- Data, Back End
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Berlin
- Working Model
- Onsite
Job Summary
In this role, you will develop data pipelines and models, manage end-to-end data products from creation to quality assurance, and mentor other data engineers within the team.
Job Technologies
Your role in the team
- 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.
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Our expectations of you
Education
- A degree in computer science, engineering, or a related field; equivalent expertise proven through experience and impact is equally valued.
Qualifications
- 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.
Experience
- Senior-level experience delivering and operating data products or backend systems end-to-end in a cloud environment such as AWS, GCP, or Azure.
- Effective communication with non-engineers, a genuine ownership mindset, and experience mentoring data engineers across different seniority levels.
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What we offer
- 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 will work within the Data Engineering discipline, reporting to a Data Engineering Manager and embedded on a daily basis 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.
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Benefits
Health, Fitness & Fun
Work-Life-Integration
Food & Drink
More net
Topics that you deal with on the job
Job Locations
This is your employer
Axel Springer SE
As a leading European digital publisher, Axel Springer SE offers an impressive range of successful journalistic content and marketing portals.
Description
- Company Size
- 250+ Employees
- Company Type
- Established Company
- Working Model
- Full Remote, Hybrid, Onsite
- Industry
- Media, Publishing
Employer reviews
by devworkplaces.com
Total
(1 Review)3.4
Career Growth
3.2Culture
3.2Engineering
3.7Workingconditions
3.6
Senior Data Engineer
- Location
- Berlin
- Working Model
- Onsite
- Diversity
- Open for all genders
- English Only
- English only required
