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# Data Engineer

- **Company:** Visium SA
- **Location:** Barcelona, Spain
- **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:** July 20, 2026
- **Apply:** https://www.adzuna.es/contact-us.html

## 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 and French is a must

## 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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