Data Analytics Engineer JP055109

We are looking for an experienced Data Analytics Engineer with proven hands-on experience delivering complex data projects.

In this role you will be involved throughout the entire data lifecycle from data analysis and modelling to workflow orchestration data quality monitoring and performance optimisation.

• Design build and maintain robust data pipelines.
• Support the ingestion of data from multiple source systems into a hybrid data platform.
• Work with both:
  • An on-premises Enterprise Data Warehouse (EDW) based on Data Vault methodology
  • A cloud-based data platform using a Medallion Architecture
• Perform data analysis modelling and transformation.
• Ensure data quality and optimise data pipeline performance.
• Work with stakeholders to identify and define meaningful KPIs for reporting.
• Implement KPIs data models and reporting solutions.
• Contribute to data migration and integration initiatives.
• Work pragmatically within an Agile environment.

We are looking for a strong Data Analytics Engineer with hands-on experience in:

• SQL Expert level
• Power BI Expert level
• dbt
• Data Vault 2.0
• Dimensional Modelling / Kimball
• ETL pipelines and data mapping
• Enterprise Data Warehousing
• Microsoft Fabric
• Databricks
• DAX
• Python
• Jinja
• Azure DevOps
• Data Migration
• Agile ways of working

You should also have recent proven experience as both an Analytics Engineer and a Power BI Business Analyst.

The following certifications are highly desirable:

• Microsoft Fabric Analytics Engineer Associate
• Microsoft Power BI Data Analyst
• Azure Fundamentals
• Collibra Data Steward Learning Path
• dbt Fundamentals
• Scrum Product Owner

A Masters degree is also required.

Dutch Active knowledge
French Active knowledge
English Active knowledge

Location: Brussels Belgium
Work model: Hybrid
Start date: 7 September 2026
End date: 31 December 2026
Duration: 4 months
Workload: Full-time
Daily rate: 750980

Along with the CV candidates must provide an answer explaining how they have previously identified which KPIs were important for reporting and how they implemented those KPIs. Applications without an adequate response may not be considered.

If you have strong expertise in Data Engineering Analytics Engineering SQL Power BI dbt Data Vault 2.0 Kimball modelling and modern data platforms we would like to hear from you.