Enterprise Data Engineer
Summary
Design and build scalable data pipelines and curated models on Databricks Lakehouse to deliver trusted KPIs and self-service analytics for Finance, HR, and Operations teams.
We're recruiting on behalf of a leading global trading firm in Amsterdam that's building their next-generation Enterprise Data Platform on Databricks Lakehouse. This is a rare opportunity to join at the ground level and shape how a world-class organization uses data.
The Role
As an Enterprise Data Engineer, you'll design curated data models, pipelines, and metrics that make data a trusted asset across Finance, People, and Business Operations.
What You'll Do
- Transform business requirements from non-technical stakeholders (i.e. CFO, HR, Operations etc.) into data products that help with decision making
- Build scalable ELT pipelines using dbt, SQL, PySpark, and Databricks
- Design curated models and semantic layers to standardize KPIs
- Implement governance and quality checks (lineage, testing, access controls)
- Deliver data products that power BI and self-service analytics
Who We're Looking For
- 4+ years of Data Engineering or Analytics Engineering experience, ideally with Finance/People/Ops data
- Experience creating data products for non-technical stakeholders
- Advanced Python (PySpark), SQL and dbt skills with analytics modeling experience (dimensional, medallion, vault)
- Hands‑on Databricks or Snowflake Lakehouse platform experience
Our client is able to provide visa sponsorship and relocation assistance for the right candidate.