Databricks Data Engineering Manager

Job Description

<p><b>Data Engineering Manager (Hands-On) – Toronto, ON</b></p><p><b>Onsite | Full-Time</b></p><p> <b>No Third-Party Contractors</b></p><p><br></p><p><b>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.</b></p><p><br></p><p><b>What You’ll Do</b></p><ul><li><b>Lead the design and operations of the Databricks Lakehouse Platform</b></li><li>Build and optimize scalable ETL/ELT pipelines using Spark (PySpark/Scala)</li><li>Manage Databricks clusters, infrastructure, and cost optimization</li><li>Implement strong data governance and security using Unity Catalog</li><li>Drive performance tuning, advanced Spark optimizations, and best practices</li><li>Lead and mentor data engineers; collaborate across business and tech teams</li><li>Oversee CI/CD workflows, Git-based development, and Infrastructure as Code</li><li>Establish monitoring, SLAs, KPIs, and reliability standards</li></ul><p><br></p><p><b>What We’re Looking For</b></p><ul><li>5+ years of hands-on Databricks + Spark experience</li><li>Strong background in AWS (S3, Glue, Lambda, EMR, Step Functions)</li><li>Advanced Python (PySpark) or Scala skills, plus strong SQL</li><li>Experience with Terraform/CloudFormation and CI/CD pipelines</li><li>Solid understanding of data warehousing & modeling</li><li>Proven leadership experience in fast-paced environments</li><li>Experience using <b>AI</b> in the development lifecycle is a plus</li><li>Financial industry experience preferred</li><li>Ability to travel to the U.S. occasionally</li></ul><p></p>