Data Engineering Manager (Hands-On) – Toronto, ONOnsite | Full-Time No Third-Party Contractors
Our client is seeking a hands-on Data Engineering Manager to lead and grow a high-performing data engineering team while remaining deeply technical. This role focuses on architecting and optimizing large-scale data solutions on Databricks integrated with AWS.
What You’ll DoLead the design and operations of the Databricks Lakehouse PlatformBuild and optimize scalable ETL/ELT pipelines using Spark (PySpark/Scala)Manage Databricks clusters, infrastructure, and cost optimizationImplement strong data governance and security using Unity CatalogDrive performance tuning, advanced Spark optimizations, and best practicesLead and mentor data engineers; collaborate across business and tech teamsOversee CI/CD workflows, Git-based development, and Infrastructure as CodeEstablish monitoring, SLAs, KPIs, and reliability standards
What We’re Looking For5+ years of hands-on Databricks + Spark experienceStrong background in AWS (S3, Glue, Lambda, EMR, Step Functions)Advanced Python (PySpark) or Scala skills, plus strong SQLExperience with Terraform/CloudFormation and CI/CD pipelinesSolid understanding of data warehousing & modelingProven leadership experience in fast-paced environmentsExperience using AI in the development lifecycle is a plusFinancial industry experience preferredAbility to travel to the U.S. occasionally
Data Engineering Manager (Hands-On) – Toronto, ONOnsite | Full-Time No Third-Party Contractors
Our client is seeking a hands-on Data Engineering Manager to lead and grow a high-performing data engineering team while remaining deeply technical. This role focuses on architecting and optimizing large-scale data solutions on Databricks integrated with AWS.
What You’ll DoLead the design and operations of the Databricks Lakehouse PlatformBuild and optimize scalable ETL/ELT pipelines using Spark (PySpark/Scala)Manage Databricks clusters, infrastructure, and cost optimizationImplement strong data governance and security using Unity CatalogDrive performance tuning, advanced Spark optimizations, and best practicesLead and mentor data engineers; collaborate across business and tech teamsOversee CI/CD workflows, Git-based development, and Infrastructure as CodeEstablish monitoring, SLAs, KPIs, and reliability standards
What We’re Looking For5+ years of hands-on Databricks + Spark experienceStrong background in AWS (S3, Glue, Lambda, EMR, Step Functions)Advanced Python (PySpark) or Scala skills, plus strong SQLExperience with Terraform/CloudFormation and CI/CD pipelinesSolid understanding of data warehousing & modelingProven leadership experience in fast-paced environmentsExperience using AI in the development lifecycle is a plusFinancial industry experience preferredAbility to travel to the U.S. occasionally
Data Engineering Manager (Hands-On) - Toronto, ON Onsite Full-Time No Third-Party Contractors
Our client is seeking a hands-on Data Engineering Manager to lead and grow a high-performing data engineering team while remaining deeply technical. This role focuses on architecting and optimizing large-scale data solutions on Databricks integrated with AWS.
What You'll Do Lead the design and operations of the Databricks Lakehouse Platform Build and optimize scalable ETL/ELT pipelines using Spark (PySpark/Scala) Manage Databricks clusters, infrastructure, and cost optimization Implement strong data governance and security using Unity Catalog Drive performance tuning, advanced Spark optimizations, and best practices Lead and mentor data engineers; collaborate across business and tech teams Oversee CI/CD workflows, Git-based development, and Infrastructure as Code Establish monitoring, SLAs, KPIs, and reliability standards
What We're Looking For 5+ years of hands-on Databricks + Spark experience Strong background in AWS (S3, Glue, Lambda, EMR, Step Functions) Advanced Python (PySpark) or Scala skills, plus strong SQL Experience with Terraform/CloudFormation and CI/CD pipelines Solid understanding of data warehousing & modeling Proven leadership experience in fast-paced environments Experience using AI in the development lifecycle is a plus Financial industry experience preferred Ability to travel to the U.S. occasionally
