Beschreibung
We are looking for a (Senior) Data Engineer (m/f/d)
(unlimited, full-time) Join our team at our location in Berlin – hybrid working conditions available
## Your Mission:
As part of our Data Engineering team, you’ll design, build, and maintain robust data pipelines using Azure Data Factory, Databricks, Airflow, and other cloud-native tools. You'll shape how we ingest, transform, and serve data across our organization—powering analytics, reporting, and decision-making at scale.
This is a han...
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We are looking for a (Senior) Data Engineer (m/f/d)
(unlimited, full-time) Join our team at our location in Berlin – hybrid working conditions available
## Your Mission:
As part of our Data Engineering team, you’ll design, build, and maintain robust data pipelines using Azure Data Factory, Databricks, Airflow, and other cloud-native tools. You'll shape how we ingest, transform, and serve data across our organization—powering analytics, reporting, and decision-making at scale.
This is a hands-on, impact-driven role for someone who enjoys working across big data, cloud platforms, and data infrastructure. You’ll collaborate with product, analytics, and engineering teams across countries and functions.
## What you are expected to do:
- 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.
## What you should bring:
- Bachelor’s or Master’s 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.