Data Engineer: Build Scalable Pipelines & Data Platforms

Cream Consulting; Brussel Hoofdstad; Sur place; EUR 45 000 - 65 000; Plein temps

Avantages offerts par ce poste

Mobility plan

Meal vouchers

Insurances

Résumé du poste

Cream Consulting is seeking a Data Engineer to design and maintain scalable data architectures in Brussels. You will build ETL/ELT pipelines and collaborate with analysts and business teams to leverage data effectively.

Required 2+ years in data engineering, strong SQL skills, and experience with Python. Proficiency in Azure Data Factory, Spark, and Databricks is a plus. French and English fluency are essential.

Qualifications

• At least 2 years of experience in data engineering.
• Master’s degree in IT or Business Administration, or equivalent by experience (around 5 years).
• Strong experience with SQL and data pipeline development.
• Knowledge of Python or other programming languages used for data processing.
• Good understanding of database systems (SQL and NoSQL).
• Fluent in French and English; a good level of Dutch is an asset.

Responsabilités

• Design and develop scalable data architectures (data warehouses, data lakes, data marts).
• Build and maintain efficient ETL/ELT pipelines.
• Ensure data quality, reliability and performance across systems.
• Optimize data processing and storage solutions.
• Implement data security and governance best practices.
• Collaborate with data analysts, data scientists and business teams to understand data needs.
• Contribute to the selection and implementation of modern data technologies.

Connaissances

Analytical thinking

Attention to detail

Problem-solving

French (Fluent)

English (Fluent)

Dutch (Basic)

Python

Formation

Master’s degree in IT or Business Administration

Outils

Azure Data Factory

AWS

Apache Spark

SSIS

Databricks

Description du poste

Cream Consulting is seeking a Data Engineer to design and maintain scalable data architectures in Brussels. You will build ETL/ELT pipelines and collaborate with analysts and business teams to leverage data effectively.

Required 2+ years in data engineering, strong SQL skills, and experience with Python. Proficiency in Azure Data Factory, Spark, and Databricks is a plus. French and English fluency are essential.