Data Engineer – Defence, AI & Data Platforms

Capgemini; Diegem; On-site; EUR 60,000 - 90,000; Full time

Job summary

Capgemini Belgium is seeking a Data Engineer to design and build scalable data pipelines and architectures for analytics and ML workloads. You will work with Python, SQL, Spark, and Docker to create robust data processing solutions and to maintain CI/CD pipelines using Jenkins, Jupyter, Superset, and Dagster.

You’ll collaborate with data scientists, software engineers, and operations, contributing to continuous improvement of data engineering standards while leveraging open-source and

Qualifications

• Master's degree in Computer Science, Engineering, Informatics or related field with Data Engineering/Sda related specialization.
• 3–5 years of solid data engineering experience.
• Proficient in Python, SQL, Spark, and Docker for data processing and automation.
• Familiar with Jenkins, Jupyter, Superset, and Dagster; experience with data warehousing and Kubeflow is a plus.
• Solid understanding of databases, data lakes, data warehouses, CI/CD pipelines, and unit testing; interest in open-source and on-premises solutions.

Responsibilities

• Design, develop, deploy, validate, and test data pipelines and architectures to support engineering and analytics needs.
• Define and implement data architectures, set up databases, data lakes, and storage for structured and unstructured data.
• Develop data pipelines to support ML workflows using Python, SQL, Spark, and Docker.
• Manage and improve CI/CD pipelines to automate testing and deployment, using Jenkins, Jupyter, Superset, and Dagster.
• Collaborate with software engineers, data scientists, and engineers to ensure data systems meet project requirements and support multiple projects.

Skills

Python

SQL

Spark

Docker

Jenkins

Jupyter

Superset

Dagster

Kubeflow

Git

Education

Master's degree in Computer Science/Engineering/Informatics

Tools

Kubeflow

Job description

Capgemini Belgium is seeking a Data Engineer to design and build scalable data pipelines and architectures for analytics and ML workloads. You will work with Python, SQL, Spark, and Docker to create robust data processing solutions and to maintain CI/CD pipelines using Jenkins, Jupyter, Superset, and Dagster.

You’ll collaborate with data scientists, software engineers, and operations, contributing to continuous improvement of data engineering standards while leveraging open-source and