> Markdown version of [/jobs/ext/3943896-data-engineer-defense](https://www.wearedevelopers.com/jobs/ext/3943896-data-engineer-defense). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Engineer | Defense

- **Company:** Capgemini
- **Location:** Diegem (Machelen), Belgium
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Automation of Tests, Unit Testing, C++ (Programming Language), Software Quality, Databases, Continuous Integration, Data Architecture, Information Engineering, Data Structures, Data Systems, Data Warehousing, DevOps, Python (Programming Language), MATLAB, Machine Learning, Open Source Technology, Software Tools, Software Engineering, SQL Databases, Strategies of Testing, Unstructured Data, Data Processing, Apache Spark, Jupyter, Git, Data Lakes, Kubernetes, Information Technology, Data Analytics, Bitbucket, Front End Software Development, Data Pipelines, Docker, Jenkins
- **Published:** October 27, 2026
- **Apply:** https://www.capgemini.com/jobs/584881-en_GB_SAPBTP/x/

## About the Role

* You hold a Master's degree in Computer Science, Engineering, Informatics, or an equivalent field, ideally with a specialisation in Data Engineering, Data Science, or a related discipline, and bring 3 to 5 years of solid experience in data engineering
 * You are proficient in Python, SQL, Spark, and Docker, particularly for data processing, AI applications, and automation, and are familiar with data engineering tools and frameworks such as Jenkins, Jupyter, Superset, and Dagster; experience with data warehousing and Kubeflow is considered a plus
 * You have a good understanding of databases, data lakes, data warehouses, CI/CD pipelines, and unit testing practices, with a strong interest in open-source and on-premises solutions
 * Additional knowledge in software engineering, frontend development, data analytics, C/C++, Git, DevOps, and Bitbucket would be considered an advantage, as would knowledge of MATLAB unit testing

## Description

* Designing, developing, deploying, validating, and testing data pipelines and data architectures to support engineering and analytics needs, ensuring consistency, scalability, and performance across platforms
 * Defining and implementing efficient data architecture and data structures, setting up, maintaining, and optimising databases, data lakes, and related storage solutions for both structured and unstructured data
 * Developing data pipelines to support the execution of machine learning algorithms and other advanced data processing workflows, leveraging tools such as Python, SQL, Spark, and Docker
 * Managing and improving CI/CD pipelines to automate testing and deployment processes, improve code quality, and enhance development efficiency, using frameworks such as Jenkins, Jupyter, Superset, and Dagster
 * Collaborating closely with software developers, data scientists, and engineers to ensure data systems meet project and business requirements, actively supporting multiple projects and working with Operations and inline production services to enhance the performance of defence systems
 * Contributing to the continuous improvement of development practices, testing strategies, and data engineering standards, staying informed about the latest trends and innovations in data engineering and open-source solutions