Job
- Level
- Senior
- Job Feld
- Data, Back End
- Anstellung
- Vollzeit
- Vertragsart
- Unbefristetes Dienstverhältnis
- Ort
- Berlin
- Arbeitsmodell
- Onsite
Job Zusammenfassung
In diesem Job entwickelst du Datenpipelines und -modelle, betreust End-to-End-Datenprodukte von der Erstellung bis zur Qualitätssicherung und mentorst andere Dateningenieure im Team.
Job Technologien
Deine Rolle im 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.
Unsere Erwartungen an dich
Ausbildung
- A degree in computer science, engineering, or a related field; equivalent expertise proven through experience and impact is equally valued.
Qualifikationen
- 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.
Erfahrung
- 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.
Unser Angebot
- 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.
Benefits
Gesundheit, Fitness & Fun
Work-Life-Integration
Essen & Trinken
Mehr Netto
Themen mit denen du dich im Job beschäftigst
Job Standorte
Das ist dein Arbeitgeber
Axel Springer SE
Als führender europäischer Digitalverlag bietet die Axel Springer SE eine beeindruckende Palette an erfolgreichen journalistischen Inhalten und Vermarktungs- sowie Rubrikenportalen.
Description
- Unternehmensgröße
- 250+ Employees
- Unternehmenstyp
- Etablierte Firma
- Arbeitsmodell
- Full Remote, Hybrid, Onsite
- Branche
- Medien, Verlagswesen
Arbeitgeber-Reviews
von devworkplaces.com
Gesamt
(1 Bewertung)3.4
Career Growth
3.2Culture
3.2Engineering
3.7Workingconditions
3.6
Senior Data Engineer
- Ort
- Berlin
- Arbeitsmodell
- Onsite
- Diversität
- Für alle Personen geeignet (m/w/d)
- Nur Englisch
- Nur Englisch erforderlich
