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# Senior Data Engineer (Databricks)

- **Company:** Visium SA
- **Location:** München, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Systems, Data Warehousing, Distributed Computing Environment, Distributed Data Store, Python (Programming Language), Apache Spark, Microsoft Fabric, Data Lakes, Data Management, Databricks
- **Published:** September 4, 2026
- **Apply:** https://www.adzuna.de/details/5867128809

## About the Role

In order to apply, this should be part of your background:

 * 5+ years in Data Engineering with expertise in Data Platforms, Data Modeling, and building production-grade pipelines
 * Strong ability to translate business requirements to tech solutions
 * Experience with either Databricks or Microsoft Fabric is required; experience with both is a strong advantage.
 * Experience with integration of SAP data
 * Leadership mindset and experience in managing data engineering teams
 * Skilled in distributed data processing (e.g., Spark), data lakes/warehouses, ETL/ELT patterns, and Python development
 * Strong problem-solving, ownership, and consulting communication skills, able to work independently in complex environments
 * Fluency in English is a must, French/German is nice to have

## Description

As a Senior Data Engineer, you will play a key role in designing, building, and scaling modern data platforms for our clients.

You will:

 * Assess and understand clients' data landscapes, including sources, architectures, and data quality
 * Collaborate with business and IT stakeholders to translate requirements into robust data solutions
 * Design, build, and maintain scalable data platforms (pipelines, data lakes, data warehouses) on modern cloud infrastructures
 * Implement data models, schemas, and governance frameworks to support analytics and reporting needs
 * Contribute to technical sales and pre-sales activities, including solution design and estimations
 * Work with large-scale, distributed data systems, troubleshoot issues, and stay current with data engineering best practices


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