Introduction

We are looking for a (Senior) Data Engineer (m/f/d) to join our team in Berlin. Hybrid working conditions are available.

Responsibilities

Design and implement scalable ETL/ELT pipelines in a lakehouse architecture using Databricks, Azure Data Factory, Azure Data Lake, and other modern tools
Create analytical data models and structures optimized for performance and usability
Drive best practices in data engineering, including CI/CD with Azure DevOps, Git workflows, testing, and monitoring
Integrate workflows and orchestration using Airflow and other tools as needed
Troubleshoot, monitor, and improve data quality, pipeline reliability, and job performance across distributed systems
Work with stakeholders to understand data requirements and deliver scalable, maintainable solutions
Stay on top of trends in cloud data platforms, open-source frameworks, and engineering practices

Bachelors or Masters degree in Computer Science, Engineering, or a related field
5+ years of experience in data engineering, with a focus on cloud-native platforms
Hands-on expertise with Azure Data Factory, Databricks, Azure Data Lake, SQL, and Python
Familiarity with DevOps workflows (e.g., Git, Azure DevOps) and orchestration tools like Airflow
Solid understanding of data warehousing, data modeling, and modern data architecture
Strong communication skills and the ability to work cross-functionally with business and technical stakeholders
A proactive mindset, capable of owning outcomes and navigating ambiguity