Engineer monitored, governed data flows with Python and Spark for Croesus's wealth management platforms. This hybrid position requires two weekly office days in Laval or Montréal.

The Data Engineering Expert develops and operates up-to-date Databricks Lakehouse pipelines supporting analytics and artificial intelligence solutions. Responsibilities span migration, Medallion architecture, metadata management, orchestration, monitoring, and incident response. You will work with diverse technical teams to turn business requirements into reliable, well-documented models while maintaining data quality and traceability.

Key Responsibilities:

- Develop high-performing ELT/ETL pipelines using Python and Spark
- Modernize data flows through Databricks migration initiatives




- Manage governance and metadata standards across datasets
- Automate pipeline orchestration, monitoring, and production alerting
- Resolve incidents affecting production data flow performance

Requirements:

- At least five years in data engineering or analytical development
- Hands-on production Databricks experience with large data volumes
- Proficiency in Python and distributed Spark processing
- Knowledge of DataOps, DevOps, and Unity Catalog
- Strong analytical, autonomous, and collaborative working style

Apply Python, Spark, Databricks, and observability expertise to dependable data engineering at Croesus.

📌 Python Spark Data Pipeline Engineer (Laval)
🏢 Croesus
📍 Laval