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 modern 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 cooperative working style
Apply Python, Spark, Databricks, and observability expertise to dependable data engineering at Croesus.

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📌 Python Spark Data Pipeline Engineer (Quebec City)
🏢 Croesus
📍 Quebec City