Contract jobs in Canada

Explore contract jobs across Canada. Choose a location and read the full job details.

10,541 listings · 2,751 employers Counted Oct 8, 2026. How we count

About these jobs

Employers hiring include Walmart Canada (706 listings), The Byng Group (140 listings), J&M Group (139 listings).

Common roles: Project manager, Sales representative, Software engineer.

2,203 of these listings include employer-provided pay. Open a job to see its currency and pay period.

Advertised starting pay
Pay period	Median starting pay	Listings
CAD / hour	36.92	1,488
CAD / year	65,079.00	471
USD / hour	42.00	101
USD / year	45,500.00	32

Employer-listed minimums from at least 10 listings per currency and pay period. These are advertised starting amounts, not employee salaries. Jobs without a minimum and unusual amounts are excluded.

Workplace classifications: 4% remote, 23% hybrid, 73% on-site, 0% not specified. Hybrid and on-site classifications may be inferred from descriptions. Check the original ad.

Based on the dated count above. Listings can change. How we count

Contract jobs in Canada

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Added 1 day ago
VB
Senior Financial Analyst, Contract
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- $45 to $60 CAD / hour
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TI
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IS
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RT
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UO
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A
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Altis
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IS
Senior Data Engineer
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Mississauga, ON
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Green Shield Canada
London, ON · Toronto, ON · Windsor, ON
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US
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Toronto, ON
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BGC St. Alban's Club
Toronto, ON · North York, Ontario
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AM
Cost Estimator
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Toronto, ON · Scarborough, Ontario
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Toronto, ON
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LC
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Loblaw Companies Limited
Brampton, ON
- Full-time
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PC
Security Guard
Pathway Communications
Markham, ON
- Contract
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Term EA Assignment FTE 0.5
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Orleans, ON
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Added 1 day ago
D
Electrician
Dexian
Nisku, AB
- $40 to $44 CAD / hour
- Contract

Hire DigITalent Inc.

Databricks Engineer

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

$90 to $110 CAD / hour · Contract

Apply About employer

Applications open in a new tab.

Job details

Pay: $90 to $110 CAD / hour
Job type: Contract
Apply by: Nov 5, 2026
Experience: 5+ years of professional experience in data engineering or data platform development.
Posting language: English
Posted: Oct 6, 2026

Original job description

Our client is running a modern data platform built on AWS and actively moving through a major Databricks implementation. The core objective is transforming data into actionable business products for marketing and promotions. The project team needs a seasoned Senior Data Engineer to help lead the charge, stabilize key deliverables, and guide our technical strategy. This is a critical engagement on a high-visibility, fast-paced project where both strong technical hands-on capability and sharp soft skills are essential.

This is a 6 month contract based in North Toronto and requires 5 days onsite.

Key Responsibilities:

Lead the design, development, and operation of scalable, cloud-based data platforms supporting analytics and machine learning workloads.
Design and maintain high-quality data pipelines (ETL/ELT) with strong standards for reliability, observability, metadata, and lineage.
Build and operate Databricks-based data engineering solutions, including Spark, SparkSQL, and Delta Lake pipelines.
Enable and support MLOps workflows, including data pipelines, feature engineering, and integration with AWS SageMaker for model training, deployment, and monitoring.
Collaborate closely with Data Science and ML Engineering teams to transition models from experimentation to production.
Work with Data Governance and Data Management teams to ensure compliance with enterprise standards and audit requirements.
Implement and maintain data quality frameworks, monitoring, and automated validation checks.
Define and maintain enterprise data assets, data models, and transformation logic.
Perform advanced data analysis to troubleshoot complex data issues and production incidents.
Contribute to CI/CD pipelines for data and analytics workloads, including testing and deployment automation.
Provide technical mentorship to data engineers, promoting engineering best practices and code quality.
Evaluate and recommend tools and technologies for data lineage, observability, and platform scalability.
Partner with architecture and platform teams to define long-term data and ML platform strategy.
Produce clear documentation and contribute to shared engineering standards and knowledge bases.

Required Skills & Qualifications:

5+ years of professional experience in data engineering or data platform development.
Advanced proficiency in Python and SQL.
Strong experience building data platforms on AWS, including services such as Lambda, Glue, Redshift, Step Functions, CloudFormation, Athena, and related services.
Hands-on experience with Databricks, including Spark, Delta Lake, notebook-driven development, and production pipelines.
Experience enabling or supporting MLOps, including integration with AWS SageMaker for model lifecycle management.
Experience delivering CI/CD pipelines for data and analytics systems.
Strong understanding of data modeling (relational, dimensional) and performance optimization.
Experience implementing data quality, monitoring, and observability solutions.
Proficient with source control tools such as Git and collaborative development practices.
Working knowledge of Linux and scripting.
Experience with file formats (CSV, JSON, XML) and diverse data integration patterns.
Strong understanding of cloud-native architectures and emerging data technologies.
Experience managing technical debt, refactoring, and evolving systems over time.
Ability to balance short-term delivery with long-term architectural considerations.
Experience as a DBA or with Salesforce (SFDC) is an asset.
Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

Apply About employer

More about this job

Responsibilities

Lead the design, development, and operation of scalable AWS and Databricks data platforms, including reliable data pipelines, data quality controls, and production MLOps workflows integrated with SageMaker. Mentor engineers, troubleshoot production issues, contribute to CI/CD and governance practices, and help shape long-term platform strategy and engineering standards.

Requirements

Requires 5+ years of data engineering experience, advanced Python and SQL skills, and hands-on experience with AWS, Databricks, Spark, Delta Lake, and production data pipelines. Candidates should also have experience with MLOps and SageMaker, CI/CD, data modeling, data quality and observability, Git, Linux, and a bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

Skills

Databricks
Apache Spark
Delta Lake
Python
SQL
AWS
AWS SageMaker
ETL/ELT Pipelines
MLOps
CI/CD
Data Modeling
Data Quality
Data Observability
Git
Linux
Data Governance

Visa sponsorship

Not detected in the job text

Keywords

Databricks
Apache Spark
SparkSQL
Delta Lake
AWS
AWS Lambda
AWS Glue
Amazon Redshift
AWS Step Functions
AWS CloudFormation
Amazon Athena
AWS SageMaker
Python
SQL
ETL/ELT
MLOps
Feature Engineering
CI/CD
Data Modeling
Data Quality
Data Observability
Data Lineage
Data Governance
Git
Linux
CSV
JSON
XML
Machine Learning
Data Engineering

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