Data Engineer
Summary
Builds and maintains data pipelines in Python and SQL to feed a cloud-migrating data warehouse, ensuring scalable, regulatory-compliant data flows for a fintech platform.
Summary:
The primary objective of the Data Engineer role is to design and build robust data pipelines, supporting critical business initiatives across the Data Platform, and progress towards a cloud-based solution.
Main Responsibilities:
- Designing, developing, and maintaining data pipelines in collaboration with cross-functional teams.
- Leveraging expertise in Python, SQL, and Git for efficient and scalable data processing.
- Building complex data transformations to meet business and regulatory requirements.
- Continuously optimizing data flows.
- Driving CI/CD best practices within the data engineering domain.
Key Requirements:
- Minimum 2 years of proven experience as a Data Engineer.
- Experience with Data Warehouse concepts (Data Vault 2.0 and Kimball).
- Proven ability to design and implement performant data pipelines handling large data volumes.
- Proficiency in Python and SQL, utilizing Git for version control.
- Strong understanding of CI/CD principles.
- Problem-solving skills and ability to address data-related business challenges.
Nice to Have:
- Experience in the banking sector.
- Familiarity with Snowflake, Azure, or Oracle.
- Power BI experience.
- Exposure to SCRUM/Agile methodologies.
- Experience with Vaultspeed.
Other Details:
- Location: Remote work possible with a preference for candidates in Brussels, Belgium.
- Team Composition: 40 Data Engineers, Data Visualization Experts, Data Analysts, and Project Managers.
- Transition to Cloud: Progressive migration of the Data Platform to a cloud solution.
- Languages: Professional proficiency in English, Dutch or French is a plus.