Data Engineer

• Analyze, implement, and maintain ETL processes using Azure Data Factory and PySpark in Databricks.
• Design and develop high-performance data solutions based on specific functional requirements.
• Prepare and execute comprehensive testing activities to ensure the reliability of data pipelines.
• Perform bug fixing and optimization of pipelines during daily production runs.
• Gather and translate business requirements into detailed functional and technical specifications.
• Manage database modeling tasks using specialized tools such as Erwin or Visio.

What they ask

• Minimum 3 years of experience with Azure cloud data platforms including Data Lake Gen2 and Synapse.
• Minimum 3 years of experience with Databricks and Python programming for data engineering.
• Minimum 3 years of experience in Azure Data Factory and Data Flow.
• Minimum 3 years of experience in DevOps practices, including Infrastructure as Code and CI/CD.
• Minimum 3 years of experience in Power BI and semantic data modeling.
• Knowledge of data management principles such as metadata management, lineage, and data quality.
• Experience in database modeling using Erwin or Visio.
• Ability to handle analytics use cases and translate complex business requirements.
• Proactive, solution-oriented, and able to work both independently and in a collaborative team environment.
• Fluent in Dutch or French with basic knowledge of the other, and a good command of English.

Nice-to-haves.

• Experience within the insurance or financial domain.
• Experience on projects involving different technology stacks and integration aspects.
• Professional and client-friendly approach.