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Lufthansa Group

Data Engineer

Lufthansa Group
Cologne, NW500+ employeesSkilled
Full-time
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This job is at Lufthansa Group. You apply to them, not to GoAusbildung.

  • Start Date

    On request

  • Sector

    Aviation / IT

  • Salary

    Competitive salary

Listing data as of November 1, 2026

About this Apprenticeship

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.

What You'll Learn

  • 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

Requirements

  • 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
  • Familiarity with streaming data frameworks
  • Solid grasp of data modeling concepts
  • Languages & Frameworks: Scala, Python, SQL, Spark
  • Cloud & Infra: Azure Cloud Platform, Databricks, Kafka, Azure DevOps/GitHub, Terraform
  • Strong collaboration mindset working with cross-functional teams
  • High attention to detail with a strong focus on data quality, accuracy and reliability
  • Exceptional stakeholder management
  • Self-starter with strong organizational skills

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