Databricks Lakehouse Data Engineer
Summary
Designs and maintains scalable Databricks Lakehouse data pipelines (Medallion architecture, Unity Catalog) using Python and Spark to support analytics and AI for wealth management products. Hybrid role in Laval with two weekly office days, including pipeline migration, orchestration, and production support.
Build Databricks Lakehouse pipelines with Python and Spark at Croesus, working in a hybrid model with two weekly office days. Support reliable data for analytics and artificial intelligence solutions across wealth management products.
As a Data Engineering Expert, you will design and optimize scalable ELT/ETL pipelines within a modern Lakehouse environment. Your work will cover Medallion architecture, Unity Catalog governance, observability, and production support. You will also collaborate with Product, Innovation, Data, and Systems teams to create documented data models from business requirements.
Key Responsibilities:
- Design and maintain Databricks Medallion architecture pipelines
- Apply Spark distributed processing for large data volumes
- Migrate existing pipelines while optimizing storage and processing
- Implement orchestration, monitoring, alerting, and incident resolution
- Translate requirements into reliable, documented data models
Requirements:
- Minimum five years in data engineering or analytical solutions
- Bachelor's degree in a related computer science or engineering field
- Production experience with Databricks, Python, and Spark
- Knowledge of Lakehouse, ELT/ETL, and orchestration mechanisms
- Strong French proficiency for all internal meetings
Bring Databricks, Spark, governance, and production data pipeline expertise to Croesus's wealth management technology teams.