Data engineer

You will join our team of experts in data engineering. The data engineer works mainly on the engineering of (batch or near-realtime) end-to-end data pipelines on our cloud-based data platform (AWS), processing data in(to) the data lake and or warehouse (Snowflake). Data is processed to build domain-oriented data products for AI/ML, BI and data integration use cases. You’ll be part of agile, business-oriented scrum teams delivering tangible business value while respecting architectural and engineering best practices.

Your responsibilities will include:

• Build and maintain robust data pipelines that integrate multiple data sources.
• Embed Data Governance by design to ensure data quality, consistency and compliance
• Align with our data architectural principles and contribute to the implementation of our Data Product architecture.
• Collaborate with business oriented and cross-functional teams and focus on delivering new data products in scope of different use cases/projects in line with Business priorities
• Contribute to the implementation of our Data landscape and Data Product architecture

Profile / Requirements : What profile are we looking for this position

Hands-on, proven experience with (“the basics”):

• Advanced SQL
• Data modelling, dimensional modelling, Data Vault modelling (strong experience required)
• Building data pipelines with DBT & PySpark
• Snowflake
• Airflow
• JSON, Parquet
• Data processing in an AWS cloud environment: AWS services (S3, Glue, Athena, AppFlow, DMS, …) & IAM
• Agile delivery, CI/CD, Git

Experience with, notions of or profound interest in (“nice to have”):

• Qlik
• Data ingestion (e.g. CDC, API, …)
• Apache Kafka
• Apache Iceberg
• Event-based data processing
• Data product architectures
• Data quality metrics
• Data catalogue, data lineage tooling (e.g. DataHub)

Fluent in English (verbal and in writing), Dutch or French optional.