Your responsibilities will include:
- Design, build and maintain scalable data pipelines, both batch and streaming, on Azure and Databricks.
- Develop ingestion, transformation and data modelling processes using PySpark, Spark SQL and Delta Lake.
- Implement and optimise lakehouse architectures, following the medallion pattern (bronze, silver, gold).
- Orchestrate workflows with Azure Data Factory, Databricks Workflows or similar tools.
- Ensure data quality, governance, lineage and security, for example with Unity Catalog and access controls.
- Industrialise delivery through CI/CD, infrastructure as code and DataOps practices.
- Work closely with data analysts, data scientists, architects and business stakeholders within Agile teams.
What we’re looking for
The ideal candidate will have:
- At least 3 years of experience in data engineering.
- Hands-on experience with Databricks and the Azure data ecosystem, including ADLS Gen2, Data Factory, Synapse and Event Hubs.
- Strong skills in Python/PySpark and SQL.
- A good understanding of data modelling, performance tuning and distributed processing.
- Experience with Git, Azure DevOps or GitHub, and CI/CD pipelines.
- Fluent English, French and/or Dutch.
Nice to have:
- Databricks certification (Data Engineer Associate or Professional) or Azure certification (DP-203 / DP-700).
- Experience with Terraform, dbt, Kafka or Microsoft Fabric.
- Experience in banking, insurance or other regulated environments.
