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# Data Engineer

- **Company:** JEMS Group
- **Location:** Brussel, Belgium
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Continuous Integration, Data Integration, Data Integrity, DevOps, Distributed Computing Environment, Junit, Python (Programming Language), Object-Oriented Software Development, Regression Testing, Cloudera, SonarQube, SQL Databases, Technical Data Management Systems, Google Cloud, Datastax, Git, Data Analytics, Jenkins
- **Published:** September 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f93a89b7eaa07cd2

## About the Role

You are a technophile who thrives on solving puzzles and staying ahead of the curve. To succeed in this role, you should bring:

 * Technical Expertise: Proficiency in SQL and at least one object-oriented language (Python, Java, or Scala).
 * Framework Knowledge: Experience with distributed computing frameworks and a solid grasp of both relational and non-relational modelling.
 * DevOps Mindset: A strong understanding of continuous integration tools such as Git, JUnit, SonarQube, or Jenkins.
 * Cloud & Big Data: Practical experience with a major cloud provider (AWS, GCP, Azure) or a Big Data distribution (Hortonworks, Cloudera, Datastax).

 * Education & Experience: You hold a degree from an engineering school or university and have at least 3 years of experience working on large-scale data projects.
 * Soft Skills: Proactive, rigorous, and comfortable working autonomously, you know when to dive into the details and when to step back to see the bigger picture.
 * Linguistic Versatility: As this role serves our Benelux clients, fluency in French, Dutch, and English (both written and spoken) is essential.

## Description

You will oversee the entire data lifecycle, ensuring information is not only accessible but also reliable and actionable. Your key responsibilities will include:

 * End-to-End Solution Design: Participating in the full architectural journey, from initial data acquisition to final exploitation, empowering business departments to make data-driven decisions.
 * Data Integration: Identifying, collecting, and weaving together diverse datasets to solve critical business and operational problems.
 * Quality & Governance: Acting as a guardian of data integrity by implementing monitoring tools and ensuring strict adherence to governance standards.
 * Bridging the Gap: Translating boardroom ambitions into clear, technical data rules, effectively connecting business needs with server-room reality.
 * Industrialisation: Scaling your achievements through robust deployment practices, including unit, integration, and non-regression testing.