Job Description

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

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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