Python Spark Data Pipeline Engineer
Croesus
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 SparkModernize data flows through Databricks migration initiativesManage governance and metadata standards across datasetsAutomate pipeline orchestration, monitoring, and production alertingResolve incidents affecting production data flow performanceRequirements:
At least five years in data engineering or analytical developmentHands-on production Databricks experience with large data volumesProficiency in Python and distributed Spark processingKnowledge of DataOps, DevOps, and Unity CatalogStrong analytical, autonomous, and collaborative working styleApply Python, Spark, Databricks, and observability expertise to dependable data engineering at Croesus.
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Develop high-performing ELT/ETL pipelines using Python and SparkModernize data flows through Databricks migration initiativesManage governance and metadata standards across datasetsAutomate pipeline orchestration, monitoring, and production alertingResolve incidents affecting production data flow performanceRequirements:
At least five years in data engineering or analytical developmentHands-on production Databricks experience with large data volumesProficiency in Python and distributed Spark processingKnowledge of DataOps, DevOps, and Unity CatalogStrong analytical, autonomous, and collaborative working styleApply Python, Spark, Databricks, and observability expertise to dependable data engineering at Croesus.
#J-18808-Ljbffr
Vacancy posted 1 hour ago
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