Senior Databricks Developer
$75 - $95 per hourGlobal Technical Talent
Databricks DeveloperLocation:
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 SummaryOur 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 ClientThis 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 GTTGTT 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.
---
Job Number: 26-15050
Industry:
Software Engineering
#LI-Hybrid #LI-GTT #gttca
#J-18808-Ljbffr
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 SummaryOur 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 ClientThis 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 GTTGTT 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.
---
Job Number: 26-15050
Industry:
Software Engineering
#LI-Hybrid #LI-GTT #gttca
#J-18808-Ljbffr
Vacancy posted 1 hour ago
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