Data engineer Azure Databricks
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As a Data Engineer specialized in Azure Databricks, you’ll play a key role in building and maintaining data pipelines, efficient storage structures, and data exchange endpoints for the benefit of business stakeholders.
In concrete terms, you will:
Design, develop, and maintain data pipelines using Azure Databricks, Azure Data Factory, Azure Functions, and Azure Stream/Log Analytics.
Implement data enrichments and transformations with Python in a Databricks environment.
Create efficient storage structures and powerful materialized views across different analytical technologies.
Develop data exchange endpoints for end users and business teams.
Interact with data governance tools (Glossary, Modeling, Lineage, Data Quality).
Collaborate with business analysts and stakeholders to refine requirements and present reusable, integrated solutions.
Contribute to extensive testing and reinforce DevOps principles within the team.
Participate in the writing and structuring of technical documentation.
Continuously look at data in a transversal way (no silos), across the entire enterprise, to maximize coherence, reuse, and adoption.
Must have:
- 3 to 5+ years of hands‑on experience in at least 2 of the following areas: SQL Server, Azure Databricks / Azure Data Factory / Azure Functions / Azure DevOps, Python in Databricks, or emerging technologies (Redis, RabbitMQ, Neo4j, Apache Arrow…)
- Strong experience with Azure Databricks and the Azure data ecosystem.
- Solid command of Python and SQL for data engineering purposes.
- Ability to interact with business analysts and stakeholders in complex, multi‑stakeholder environments.
- Product-oriented mindset with an iterative and analytical approach to problem‑solving.
- Team player who values respect, open‑mindedness, challenge, and innovation.
- Customer-oriented with excellent communication skills.
- Fluent in English (must have) AND fluent in French and/or Dutch.
Nice to have:
- Experience with Power BI.
- Experience with SAP data integration.
- Knowledge of Azure DevOps and CI/CD practices.
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