Jobs in Pointe-Claire, QC and nearby

Jobs within 25 km of Pointe-Claire, QC, Canada. Nearby towns and cities are included. Distances are straight-line, not driving distances.

32,569 listings · 4,720 employers Counted Nov 3, 2026. How we count

About these jobs

Employers hiring include RI-MUHC | Research Institute of the MUHC | #rimuhc (1,052 listings), Loblaw Companies Limited (984 listings), Bombardier (636 listings).

Common roles: Project manager, Retail sales associate, Software developer.

2,766 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	28.00	1,537
CAD / year	79,000.00	1,037
USD / year	112,050.00	80
USD / hour	55.17	74

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: 0% remote, 33% hybrid, 67% 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

Jobs in Pointe-Claire, QC and nearby

Within 25 km

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Added 15 hours ago
S
Steel Structure and Coating Inspector
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Montreal, QC
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HT
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Montreal, QC
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CE
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Montreal, QC
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Steel Structure and Coating Inspector
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Montreal, QC
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Added 15 hours ago
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Montreal, QC
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Montreal, QC
- Full-time
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Montreal, QC
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Hays

PySpark Data Engineer

Greater Montreal Metropolitan Area, QC, Canada

Hourly Rate: $55-65/hour · Contract

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Job details

Pay: Hourly Rate: $55-65/hour
Job type: Contract
Apply by: Dec 2, 2026
Experience: 5 years of hands-on software engineering or data engineering experience.
Posting language: English
Posted: Nov 2, 2026

Original job description

Python / PySpark Data Engineer

Job Type: Contract (1 year)

Location: Montréal, QC – Hybrid (3 days onsite)

Hourly Rate: $55-65/hour

Your New Company

You will join a leading global financial services organisation that is investing in a strategic Client Data Confidentiality and data-usage monitoring platform. This platform supports the monitoring, protection and reporting of sensitive client data across multiple business areas.

Your New Role

As a Python / PySpark Data Engineer, you will develop and enhance scalable data-processing capabilities used for critical client and regulatory reporting. Your focus will be on building reliable data pipelines, integrating new data sources and applications, and improving the quality, completeness and performance of data across the monitoring platform.

You will work closely with developers in Montréal and stakeholders in New York to deliver business-critical platform enhancements.

What You Need to Do

Design and develop scalable data-processing pipelines using Python, PySpark and Databricks.
Build complex SQL and data-processing solutions on Snowflake.
Develop ingestion and transformation capabilities for multiple data sources, including relational and NoSQL databases.
Integrate data from MongoDB, KDB, and application or user-interface activity sources.
Onboard new databases and applications into the monitoring platform.
Expand monitoring coverage across additional business areas and data environments.
Implement data-quality, validation and reconciliation controls.
Ensure the completeness and accuracy of data used in client and regulatory enquiries.
Troubleshoot data-processing issues and resolve data discrepancies.
Optimise pipelines for performance, scalability, reliability and maintainability.
Collaborate with geographically distributed technical and business stakeholders.

What You’ll Need to Succeed

5 years of hands-on software engineering or data engineering experience.
Strong professional development experience with Python.
Hands-on experience building distributed data-processing solutions with PySpark.
Experience developing and maintaining data pipelines using Databricks.
Advanced SQL development skills.
Experience working with Snowflake or a comparable cloud-based data platform.
Experience integrating data from heterogeneous database technologies and application sources.
Strong understanding of data ingestion, transformation, validation and reconciliation.
Demonstrated ability to troubleshoot complex data-processing and pipeline issues.
Strong analytical and problem-solving capabilities.
Ability to collaborate effectively with developers, business stakeholders and distributed teams.
Exposure to MongoDB and KDB is considered an asset.
Experience within financial services, data confidentiality, regulatory reporting or data-usage monitoring would be an advantage.

What You’ll Get in Return

You will have the opportunity to work on a highly visible data platform supporting sensitive client information and regulatory requirements within a global financial services environment. You will collaborate with experienced technology professionals, work with a modern data stack that includes Python, PySpark, Databricks, Snowflake and multiple database technologies, and contribute to a platform with significant business impact.

What You Need to Do Now

If you’re interested in this role, click “Apply now” to forward an up-to-date copy of your CV.

If this position is not quite right for you, but you are exploring new opportunities, please contact us for a confidential discussion about your career.

This posting is for an existing vacancy with the organisation.

AI may be used to screen, assess or select applicants for the position.

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More about this job

Responsibilities

Design, build, and optimize scalable data pipelines using Python, PySpark, Databricks, and Snowflake, integrating data from relational, NoSQL, and application sources. Expand platform monitoring coverage and implement quality, validation, and reconciliation controls to ensure accurate data for client and regulatory reporting.

Requirements

Requires at least five years of software or data engineering experience, strong Python and PySpark skills, Databricks pipeline experience, and advanced SQL expertise. Candidates should have experience with Snowflake or a comparable cloud data platform, heterogeneous data integration, and troubleshooting; MongoDB, KDB, and financial services experience are assets.

Skills

Python
PySpark
Databricks
SQL
Snowflake
Data Engineering
Data Pipeline Development
Data Ingestion
Data Transformation
Data Quality
Data Validation
Data Reconciliation
MongoDB
KDB
Distributed Data Processing
Troubleshooting

Visa sponsorship

Not detected in the job text

Keywords

Python
PySpark
Databricks
Snowflake
SQL
MongoDB
KDB
Data Engineering
Data Pipelines
Distributed Data Processing
Data Ingestion
Data Transformation
Relational Databases
NoSQL Databases
Application Data
Data Quality
Data Validation
Data Reconciliation
Pipeline Optimization
Scalability
Reliability
Maintainability
Client Data Confidentiality
Regulatory Reporting
Data-Usage Monitoring
Financial Services

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