Data Engineer - Intermediate Level - Deadline 26/01/26

Proficiency in Python, Java, and modern software engineering practices;

Experience with containerisation and orchestration tools such as Docker and Kubernetes;

Hands-on experience with AI and ML libraries (e.g. scikit-learn, TensorFlow, pandas);

Familiarity with distributed data processing (e.g. Apache Kafka, Airflow);

Knowledge of DevOps tools and CI/CD workflows (e.g. Jenkins, GitHub Actions);

Ability to design system-level monitoring and observability frameworks (e.g. Grafana, Prometheus);

Experience developing and documenting technical architecture for data and analytics systems;

Capacity to communicate across technical and policy domains in a collaborative environment.;

Autonomy in delivering model-based analytics aligned with architectural and business needs.;

The following specific expertise is required:

• At least 3 years of experience in software or data engineering, including applied work in AI/ML contexts; 

• Demonstrated experience in designing and implementing full data pipelines in production environments;

• Proven capacity to deploy and monitor intelligent systems within modular and distributed architecture;

• Familiarity with real-time, event-driven, or edge-oriented system architectures;

• Contributions to the implementation of analytics infrastructure that is modular, testable, and scalable;

• Background in intelligent mobility, cloud robotics, or automation considered a strong asset..

Level : Intermediate

Delivery mode : Near Site (Brussels)

Deadline