Data & Analytics Engineer

Help write the success story of Europe's largest DHL airline, European Air Transport Leipzig GmbH (EAT). The Data & Analytics Engineer (m/f/d) bridges the gap between raw data sources and business-relevant insights. In this role, data pipelines, data models and semantic layers are developed to create a reliable foundation for business intelligence, advanced analytics and AI applications.

• Building, maintaining and optimizing scalable ETL/ELT data pipelines to integrate, transform and provide quality-assured data from different source systems.
• Designing and managing semantic layers and developing business-consistent data models and metrics in data warehouse and BI solutions.
• Implementing standards for automated data tests, monitoring, documentation and traceability of data flows to ensure data quality, consistency, data protection and compliance.
• Partnering with analysts and business departments to design self-service datasets, semantic models, dashboards and reporting solutions, and to define uniform business metrics.
• Evaluating technologies, optimizing performance and resource use, and standardizing development, version control and deployment practices to further develop the BI and analytics strategy.

• Completed university degree in business informatics, industrial engineering, computer science or a comparable qualification
• More than 5 years of relevant professional experience in comparable roles
• Sound knowledge of data warehousing, data modeling and developing scalable ETL/ELT processes; experience with incremental loading or change data capture is an advantage
• Very good SQL skills and practical experience with Python and cloud data warehouses, preferably Snowflake
• Experience developing semantic models, metrics and reporting solutions, especially with Power BI
• Familiarity with data and analytics platforms as well as Dataiku; knowledge of Skywise, Spark or PySpark is an advantage
• Experience with data quality, monitoring, documentation and data governance
• Experience with Git, code reviews and CI/CD practices for data models and BI solutions
• Understanding of the data requirements of advanced analytics and AI; knowledge of machine learning, optimization or process mining is an advantage
• Knowledge of the aviation industry and its operational processes, for example in flight operations, maintenance or logistics, is an advantage
• Very good German and English skills, spoken and written
• High level of professionalism and integrity