Full-stack Data Engineering Specialist (hybrid)

Morgan Stanley

Montreal, Canada
On-site
Java/scala, python, and sql
Apache spark and azure databricks
Cloud technologies (azure, aws, or gcp)
Build end-to-end systems from data sourcing to reporting using cutting-edge big data technologies

Job Summary

  • Build end-to-end systems from data sourcing to reporting using cutting-edge big data technologies.
  • Work with a global team on complex, high-impact projects in the financial sector.
  • The department renovates the platform with focus on efficiency, simplification, consolidation and modernization.

Matching Summary

Build end-to-end systems from data sourcing to reporting using cutting-edge big data technologies.

Skills & Requirements

Must-have

  • Java/Scala, Python, and SQL
  • Apache Spark and Azure Databricks
  • Cloud technologies (Azure, AWS, or GCP)
  • Data pipelines and ETL/ELT development
  • DevOps automation and CI/CD pipelines

Nice-to-have

  • Power BI reporting knowledge
  • Machine learning and GenAI experience
  • Finance business knowledge

Key Requirements

  • 4 to 8 years of experience
  • At least 5 years+ relevant experience in Java/Scala, Python and SQL
  • At least 3 years+ relevant experience in large-scale data processing engines like Apache Spark or cloud compute technologies like Azure Databricks
  • At least 3 years+ relevant experience in cloud technologies (Azure, AWS or GCP)
  • At least 3 years+ relevant experience in building data pipelines and in ETL/ELT development using Airflow
  • At least 4 years+ relevant experience in databases technologies: Snowflake, DB2 and Teradata
  • At least 5 years+ relevant experience in DevOps automation and CI/CD pipelines
  • Knowledge of French and English is required

Work Rights

Not specified

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