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# Data Analytics Engineer Job ID: JP055023

- **Company:** ITProposal
- **Location:** Brussel, Belgium
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Big Data, Business Process Model and Notation, Data Infrastructure, Data Systems, Dimensional Modeling, Information Lifecycle Management, Python (Programming Language), PostgreSQL, Performance Tuning, Power BI, Standard Sql, SAS (Software), SQL Databases, Tableau (Software), UML, Apache Spark, Git, Pandas, Microsoft Fabric, Vba Programming Language, Data Analytics, Data Pipelines, Databricks
- **Published:** August 9, 2026
- **Apply:** https://www.careerjet.be/jobad/be0d723304842a67f4c87b12cc12f5c37f

## About the Role

* Expert knowledge of SQL, Power BI, DAX, dbt, Microsoft Fabric, Databricks, Python (Pandas, Apache Spark), Git, and PostgreSQL.
 * Experience with Airbyte, Power Platform, Tableau, SAS, UML, VBA, and BPMN.
 * Strong data modeling and analytics experience.
 * Experience with API documentation and functional/technical analysis.
 * Master's degree or equivalent experience.
 * Experience in public sector or social security projects is an advantage.
 * DP-600, dbt Developer, or Power BI Data Analytics Associate certifications are a plus.

Languages

 * Dutch: Active knowledge
 * French: Active knowledge
 * English: Passive knowledge

## Description

We are looking for an experienced Data Analytics Engineer to design, build, and optimize modern data solutions across the full data lifecycle. You will work with large-scale data platforms, develop robust data pipelines, and deliver high-quality analytics and reporting solutions., * Design, develop, and maintain scalable data pipelines and workflows.

 * Build and optimize data models using SQL, dbt, and Kimball dimensional modeling.
 * Ingest and transform data from multiple source systems into a Databricks data platform.
 * Develop dashboards and executive reports using Power BI.
 * Ensure data quality, governance, monitoring, and performance optimization.
 * Collaborate with business and technical stakeholders to gather requirements and define KPIs.
 * Work in an Agile environment and contribute throughout the entire data lifecycle.


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