Data Analytics Engineer – Databricks & dbt

Editx; Brussel; Sur place; EUR 65 000 - 90 000; Plein temps

Résumé du poste

Editx is seeking a data engineering professional in Belgium to design and maintain robust data pipelines using Databricks and medallion architecture.

You will develop SQL-based transformations with dbt, implement Kimball dimensional modeling for star schemas, and build executive dashboards in Power BI. Collaboration with teams will optimize data platform performance and governance.

Qualifications

• Strong experience building data pipelines and data models.
• Hands-on SQL development and data quality testing.
• Familiarity with Databricks, dbt, and Power BI.
• Ability to work with API documentation and business requirements.

Responsabilités

• Design, build, and maintain robust data pipelines using Databricks and medallion architecture.
• Develop SQL-based transformations and data quality tests with dbt.
• Implement Kimball dimensional modeling to create star schemas for performance-driven querying.
• Build dashboards and reporting solutions for executives using Power BI and DAX.
• Perform functional and technical analyses by interpreting API documentation and business requirements.
• Collaborate with technical teams and stakeholders to optimize data platform performance and governance.

Connaissances

SQL

Data Pipelines

Data Quality

Governance

Stakeholder Collaboration

Outils

Databricks

dbt

Power BI

DAX

Description du poste

Responsibilities

• Design, build, and maintain robust data pipelines using Databricks and the medallion architecture.
  


• Develop SQL-based transformations and data quality tests using dbt to ensure data integrity across layers.
  


• Implement Kimball dimensional modeling to create business-ready star schemas for performance-driven querying.
  


• Build and manage complex dashboards and reporting solutions for executive levels using Power BI and DAX.
  


• Perform functional and technical analyses by interpreting API documentation and business requirements.
  


• Collaborate with technical teams and stakeholders to optimize data platform performance and governance.