Databricks Engineer — Hybrid, AI-Driven Data Platforms

Koda Tech; Vlaams-Brabant; Hybride; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Koda Tech in Belgium (Vlaams-Brabant) is seeking an experienced Databricks Engineer to design and deliver modern cloud-based data platforms enabling analytics, AI and data-driven decisions for enterprise clients.

You will work on large-scale data transformation projects using Databricks, Apache Spark, Delta Lake and Unity Catalog, collaborating with data scientists, architects and business stakeholders to build scalable, reliable data products in a hybrid work environment.

Qualifications

• Proven experience with Databricks in production environments.
• Strong knowledge of Spark, Delta Lake and Unity Catalog.
• Experience with IaC, CI/CD and version control.
• Experience on Azure or AWS cloud environments.
• Fluent Dutch (spoken and written).

Responsabilités

• Design, build and maintain scalable data platforms using Databricks.
• Develop robust data pipelines ingesting data from multiple systems.
• Build and optimise data solutions with Spark, Delta Lake and Unity Catalog.
• Ensure data reliability and accessibility for analytics and AI.
• Contribute to platform architecture decisions and best practices.
• Apply software engineering practices including testing, version control, and CI/CD.
• Collaborate with stakeholders to deliver high-value data products.
• Explore AI-driven capabilities to improve development efficiency and performance.

Connaissances

Python

SQL

Dutch language

Problem solving

Stakeholder empathy

Outils

Databricks

Apache Spark

Delta Lake

Unity Catalog

IaC

Git

CI/CD

Azure

AWS

Description du poste

Koda Tech in Belgium (Vlaams-Brabant) is seeking an experienced Databricks Engineer to design and deliver modern cloud-based data platforms enabling analytics, AI and data-driven decisions for enterprise clients.

You will work on large-scale data transformation projects using Databricks, Apache Spark, Delta Lake and Unity Catalog, collaborating with data scientists, architects and business stakeholders to build scalable, reliable data products in a hybrid work environment.