Job
- Level
- Senior
- Job Field
- Data, Back End
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Cologne
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you will develop robust data pipelines, design scalable transformation logic, and implement MLOps infrastructure for machine learning workflows while collaborating closely with data scientists.
Job Technologies
Your role in the team
- We are looking for a versatile, senior Data / ML Engineer to join us. You will sit at the critical intersection of Data Engineering and Machine Learning, serving as the bridge between raw data infrastructure and production-ready AI models.
- This role requires a pragmatic engineering mindset. You will be responsible for architecting robust data pipelines, designing scalable transformation logic, and building the MLOps infrastructure required to deploy, monitor, and scale machine learning workflows in production.
- Design, build, and maintain scalable, fault-tolerant data pipelines (ETL/ELT) to ingest and process large-scale structured and unstructured data using Spark and cloud-native architectures.
- Collaborate closely with Data Scientists to transition experimental models into clean, production-ready code and robust pipelines.
- Implement advanced data modeling and transformation logic to ensure high-fidelity inputs for both downstream models and business analytics.
- Build continuous integration and deployment (CI/CD) pipelines for data and ML workflows, ensuring system reliability, data quality, and uptime.
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Our expectations of you
Qualifications
- Deep understanding of data pipeline orchestration, distributed processing, and building resilient, testable ETL/ELT systems.
- Solid grasp of data modeling concepts, especially in the context of analytics and reporting (conceptual, logical, and physical models).
- Vertrautheit mit Streaming-Daten-Frameworks (Kafka, Event Hubs oder ähnliches).
- Ability to explain complex technical concepts to both technical and non-technical stakeholders.
- Strong ability to work effectively with cross-functional teams including data science, engineering, and business units.
- Skilled in balancing immediate business needs with long-term technical feasibility.
- High attention to detail with a strong focus on data quality, accuracy, and reliability.
- A self-starter with strong organizational skills and the ability to drive initiatives from concept to completion.
Experience
- 7+ years of experience in data engineering, ideally with hands-on exposure to analytics engineering practices (e.g., data modeling, transformation logic).
- Proven experience working closely with data scientists or driving data science projects with a highly pragmatic, production-focused mindset.
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Benefits
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Job Locations
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Eurowings Aviation GmbH
At Eurowings, we strive to provide our customers with a seamless travel experience. That's why we're working hard to create the digital travel companion of the future. It will support our customers throughout their journey with relevant information and smart services, from inspiration with "Horizons by Eurowings" to memories of their trip!
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Logistics, Transportation