Our Data Engineering team plays a critical role in this mission, transforming raw data into high-quality, reliable assets for reporting, analytics, and advanced data products. You'll be part of a collaborative team of Data Engineers, and supported by a dedicated Data Architect and Program Manager for alignment across tech and business.
FACTS
Location
Cologne
Employment level
Direct entry
Function
IT
Working time
Full time
Tasks
What you'll do
* Design, build, and maintain reliable and scalable data pipelines to support analytics, reporting, and future ML use cases
* Contribute to our modern cloud-based data platform in Azure and Databricks
* Collaborate closely with Data Analysts and Data Scientists to co-create data products
* Support and contribute to our internal data platform alongside our Data Platform Engineer
* Continuously improve data quality, documentation, and performance
* Champion best practices in DataOps: CI/CD, monitoring, alerting, testing, and infrastructure-as-code
Behind the scenes
We are dreamers, doers, and enthusiasts...
Our mission is to enable our customers on leisure and/or business travel to enjoy a seamless travel booking experience from the tip of their fingers.
Requirements
What you'll need
* 7+ years of experience in data engineering, ideally with some hands-on exposure to analytics engineering practices (e.g., data modeling, transformation logic)
* Deep understanding of data pipeline orchestration, distributed processing, and building resilient, testable ETL/ELT systems
* Expertise in Scala or Python with strong SQL skills and experience using Spark in production environments
* Experience with cloud-native architectures, especially Azure Cloud Platform and Databricks
* Familiarity with streaming data frameworks (Kafka, Event Hubs, or similar)
* Solid grasp of data modeling concepts, especially in the context of analytics and reporting (conceptual/logical/physical models)
What you'll bring
* Excellent communication skills with the ability to explain complex technical concepts to stakeholders
* Strong collaboration mindset to work effectively with cross-functional teams including data science, engineering, and business units
* High attention to detail with a strong focus on data quality, accuracy, and reliability
* Self-starter with strong organizational skills
Company