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Senior Data Engineer Azure Data Factory Developer (35968)

Toronto, ON, Canada

Contract

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The original listing is kept below for reference.

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Job details

Job type: Contract
Closing date: Nov 4, 2026
Posting language: English
Posted: Oct 5, 2026

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Original job description

Archived listing. The details below describe a past opening.

Our client is seeking two Senior Data professionals to support a data engineering and integration initiative: one Data Engineer specializing in Databricks and Apache Spark, and one Azure Data Factory Developer focused on ETL and data integration. The engagement will include one onsite/hybrid resource in Toronto and one offshore resource, with both resources required to complete onboarding before the end of October 2026.

Role 1: Senior Data Engineer, Databricks / Apache Spark

Delivery Model: This role may be filled by either the onsite/hybrid Toronto resource or the offshore resource. Across the two positions, one resource will be onsite and one offshore.

Responsibilities

Design, develop and maintain data processing solutions using Databricks
Develop and optimize Apache Spark jobs for data transformation and processing
Build data ingestion and transformation workflows
Develop scalable, reusable and unit-tested data engineering components
Troubleshoot Databricks and Spark workloads
Support deployment, issue resolution and enhancement activities
Produce technical documentation and support knowledge transfer

Required Skills

Strong Databricks experience
Strong Apache Spark experience
Data transformation and processing
Data ingestion and pipeline development

Role 2: Senior Azure Data Factory Developer

Delivery Model: This role may be filled by either the onsite/hybrid Toronto resource or the offshore resource. Across the two positions, one resource will be onsite and one offshore.

Responsibilities

Design, build and maintain Azure Data Factory pipelines and workflows
Develop ETL and data integration solutions across source and target systems
Support integrated processing and orchestration using Databricks where required
Configure pipeline monitoring and error handling
Troubleshoot and optimize data movement and pipeline execution
Support testing, deployment and operational stabilization
Produce technical documentation and support knowledge transfer

Required Skills

Strong Azure Data Factory experience
Working knowledge of Databricks
Data integration experience
ETL pipeline development and support

About employer

More about this job

Responsibilities

Design, develop, and maintain scalable data processing, ingestion, transformation, and ETL solutions using Databricks, Apache Spark, and Azure Data Factory. Troubleshoot and optimize workloads and pipelines, support testing, deployment, and operational stabilization, and provide technical documentation and knowledge transfer.

Requirements

The roles require strong experience with Databricks and Apache Spark for the data engineering position, or strong Azure Data Factory experience for the ETL and integration position. Relevant capabilities include data ingestion, transformation, pipeline development, data integration, and, for the Azure Data Factory role, working knowledge of Databricks.

Skills

Databricks
Apache Spark
Azure Data Factory
Data Transformation
Data Processing
Data Ingestion
Data Pipeline Development
ETL
Data Integration
Pipeline Orchestration
Pipeline Monitoring
Error Handling
Unit Testing
Troubleshooting
Technical Documentation

Visa sponsorship

Not detected in the job text

Keywords

Databricks
Apache Spark
Azure Data Factory
Data Engineering
ETL
Data Integration
Data Ingestion
Data Transformation
Data Processing
Data Pipelines
Workflow Orchestration
Pipeline Monitoring
Error Handling
Unit Testing
Troubleshooting
Deployment
Operational Stabilization
Technical Documentation
Knowledge Transfer
Manufacturing

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