Senior Databricks Developer

Kardow; Toronto; Hybrid; CAD 103,000 - 131,000; Full time

Job summary

Kardow is seeking a Databricks Developer in Toronto to design, build, and support scalable data pipelines and lakehouse solutions. The role requires deep hands-on experience with Azure Databricks, PySpark, and Delta Lake, along with governance and production deployment practices.

As a senior contributor, you will collaborate across architecture, analytics and platform teams to deliver reliable, well-governed data platforms. Hybrid onsite flexibility and a 6-month contract duration are offered.

Qualifications

• 10+ years of experience in data engineering or related technical roles.
• Strong hands-on experience with Azure Databricks and PySpark/Spark SQL.
• Experience with Delta Lake and medallion architecture.
• Experience with Azure Data Factory orchestration.
• Strong data governance, RBAC, and security practices.
• Ability to communicate effectively with technical and non-technical teams.

Responsibilities

• Design, build and support scalable data pipelines using Azure Databricks.
• Develop and maintain ETL/ELT solutions with PySpark, Spark SQL and Delta Lake.
• Implement medallion/lakehouse architecture across data layers.
• Orchestrate Databricks workloads using Azure Data Factory.
• Optimize Delta tables and Spark workloads for performance and cost.
• Ensure data quality, auditing, logging and monitoring.

Skills

Azure Databricks

PySpark

Spark SQL

Delta Lake

Azure Data Factory

Databricks governance

CI/CD

Production deployment

Tools

Databricks CLI

Unity Catalog

Infrastructure as Code

Job description

Databricks Developer

Location: Toronto, ON

Onsite Flexibility: Hybrid

Contract Details

• Position Type: Contract
• Contract Duration: 6 months
• Pay Rate: C$75.00–C$95.00 / Hour (CAD)

Job Summary

Our client is seeking an experienced Senior Azure Databricks Data Engineer to design, build and support scalable enterprise data pipelines and modern lakehouse solutions. The successful candidate will bring deep hands-on experience with Azure Databricks, PySpark, Spark SQL, Delta Lake and Azure Data Factory, with a strong understanding of medallion architecture, data governance, performance optimization and production deployment. This is a senior-level engineering role requiring the ability to work across architecture, analytics, platform and delivery teams to build reliable, scalable and well-governed data solutions.

Key Responsibilities

• Design, build and support scalable data pipelines using Azure Databricks.
• Develop and maintain ETL/ELT solutions using PySpark, Spark SQL and Delta Lake.
• Implement and support medallion / lakehouse architecture across raw, curated and business-ready data layers.
• Use Azure Data Factory (ADF) to orchestrate Databricks workloads, manage dependencies and schedule pipeline execution.
• Design and optimize Delta tables and Spark workloads for performance, scalability and cost efficiency.
• Implement data quality, validation, audit, logging, monitoring and operational controls.
• Build and maintain production-ready Databricks jobs, notebooks, repositories and deployment processes.
• Support source control, CI/CD pipelines and release management for enterprise data platforms.
• Integrate Databricks with Azure services including ADLS Gen2, Azure Key Vault and ADF.
• Troubleshoot production issues and support ongoing platform stability and performance.
• Collaborate with architecture, analytics, platform and business teams to deliver scalable data solutions.
• Apply strong governance, access-control and security practices across the Databricks environment.

Required Skills

• Strong hands-on expertise with Azure Databricks.
• Advanced experience with:
• Auto Loader - Unity Catalog - Databricks SQL - Change Data Feed - Liquid Clustering - Databricks CLI - Infrastructure as Code
• Strong understanding of Databricks governance and access control, including:
• Role-based access control - Attribute-based access control - Object permissions - Row-level security - Column masking
• Strong hands-on experience with PySpark and Spark SQL.
• Experience with Delta Lake, Delta tables and medallion architecture.
• Experience working with Databricks Jobs, clusters, notebooks, repositories and production deployment patterns.
• Strong experience integrating Databricks with ADLS Gen2, Azure Key Vault and Azure Data Factory.
• Experience using ADF for orchestration, scheduling, parameterization and monitoring.
• Strong understanding of Spark performance tuning, partitioning, optimization and cost management.
• Experience with CI/CD, source control and enterprise data platform support.
• Strong troubleshooting and production-support capabilities.
• Must be able to communicate and engage with technical and non-technical teams.

Preferred Skills

• Structured Streaming
• Delta Live Tables
• Databricks Asset Bundles
• MLflow
• Genie / Agent-based Databricks capabilities
• Advanced data governance and lineage
• Advanced Databricks cost optimization
• Experience supporting large-scale enterprise lakehouse environments
• Financial Services and/or Investments domain experience

Required Experience

• 10 years of experience in data engineering, data platforms or related technical roles.

About the Client

This client is a leading financial services and banking institution operating within the Canadian market, with a presence among the top-tier banks serving clients and businesses nationwide. The organization employs a broad range of professionals — including data engineers, DevOps engineers, business analysts, and enterprise programs analysts — who collaborate across technology, finance, and operations teams to deliver enterprise-scale solutions. With a strong emphasis on regulatory compliance, data governance, and process standardization, this institution consistently draws on contractors and specialists to support complex, high-impact initiatives across its technology and banking platforms.

About GTT

GTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation, a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking, financial services, technology, life sciences, biotech, utilities, and retail sectors throughout the U.S. and Canada.