Jobs in Ontario

Jobs across Ontario, Canada. Choose a city or town to search nearby.

107,373 listings · 11,565 employers Counted Oct 7, 2026. How we count

About these jobs

Employers hiring include Loblaw Companies Limited (2,241 listings), Walmart Canada (1,980 listings), Walmart (1,415 listings).

Common roles: Retail sales associate, Project manager, Sales representative.

14,650 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 / year	80,000.00	7,409
CAD / hour	22.00	5,497
USD / year	100,000.00	592
USD / hour	19.50	343
CAD / month	5,561.68	22
CAD / week	500.00	17
GBP / hour	35.00	16

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, 19% hybrid, 81% 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 Ontario

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Added 7 hours ago
HR
Electrical Component Engineering Intern (Summer 2027, 16months)
Hitachi Rail
Toronto, ON
- $23 to $30 CAD / hour
- Full-time
Added 7 hours ago
HR
Software Analyst
Hitachi Rail
Toronto, ON
- Full-time
Added 7 hours ago
FC
Casual Courier-12
FedEx Canada
Cambridge, ON
- Part-time
Added 7 hours ago
CC
Residence Assistant (CCNM - Toronto Campus)
Canadian College of Naturopathic Medicine
Toronto, ON
- Full-time
Added 7 hours ago
HR
Hardware Test Engineering Intern (Summer 2027, 16months)
Hitachi Rail
Toronto, ON
- $23 to $30 CAD / hour
- Full-time
Added 7 hours ago
AU
Security Guard - Gatehouse
Allied Universal
Mississauga, ON
- $19 CAD / hour
- Full-time
Added 7 hours ago
AU
Security Concierge - Full time - Swing Rotation
Allied Universal
Markham, ON
- Full-time
Added 7 hours ago
AU
Security Guard – Premium Mall
Allied Universal
Toronto, ON
- $20 CAD / hour
- Full-time
Added 7 hours ago
AU
Residential Security Guard - Full time
Allied Universal
Richmond Hill, ON
- Full-time
Added 7 hours ago
D
RESIDENTIAL FIELD TECHNICIANS – Kitchener, ON
DHT
Kitchener, ON
- Full-time
Added 7 hours ago
NF
Bakery InStore Clerk Part Time Day
No Frills
Belleville, ON
- Part-time
Added 7 hours ago
PG
garage door installer
ProTech Garage Doors
Mississauga, ON
- Full-time
Added 7 hours ago
U
Warehouse Associate
UPS
Guelph, ON
- Internship
Added 7 hours ago
LC
Post Office Clerk, Hourly Part Time Flexible Shifts
Loblaw Companies Limited
London, ON
- Part-time
Added 7 hours ago
BD
glazier
Bigfoot Door
Mississauga, ON
- Full-time
Added 7 hours ago
TH
Service Desk Associate Part Time - ETOBICOKE S
The Home Depot Canada
Toronto, ON
- Part-time
Added 7 hours ago
RH
Project Coordinator / Operations Specialist - On Site - Toronto
Robert Half
Toronto, ON
- Contract
Added 7 hours ago
U
Warehouse Associate
UPS
Guelph, ON
- Internship
Added 7 hours ago
D
Store Associate
Dollarama
Toronto, ON
- Part-time
Added 7 hours ago
D
Store Associate
Dollarama
Toronto, ON
- Part-time
Added 7 hours ago
FS
HMR Clerk Part Time Evening
Fortinos Supermarket Ltd
Oakville, ON
- Part-time
Added 7 hours ago
CO
Recreation Facility Attendant
City of Barrie
Barrie, ON
- Internship
Added 7 hours ago
A
Intermediate Software Engineer
AltaML
Toronto, ON
- $90,000 to $110,000 CAD / year
- Full-time
Added 7 hours ago
WC
Stock Unloader Associate
Walmart Canada
Huntsville, ON
- Full-time
Added 7 hours ago
WC
(CAN) General Merchandise Associate Full Time
Walmart Canada
Thunder Bay, ON
- Full-time

Zodiac Solutions, Inc

Python Developer

Toronto, ON, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Nov 5, 2026
Posting language: English
Posted: Oct 6, 2026

Original job description

Role: Python Developer – Data Engineering

Location: Toronto, ON (4 days hybrid)

Fulltime

Responsibilities:

Develop and optimize data manipulation and transformation workflows using pandas and Polars.
Design, build, and maintain efficient data processing pipelines for large-scale datasets.
Optimize Python code and data workflows for performance, scalability, and memory efficiency.
Develop containerized applications using Docker and deploy scalable services using Kubernetes.
Build and maintain data pipelines integrated with ClickHouse or similar columnar databases for analytical workloads.
Design and implement event-driven architectures using NATS for asynchronous data processing and messaging.
Develop distributed computing solutions using Dask to process datasets that exceed single-machine memory limitations.
Write and maintain comprehensive unit and integration tests using pytest.
Maintain high code quality, test coverage, reliability, and performance standards.
Use Git for version control and follow established branching, code review, and collaboration practices.
Collaborate with data engineers, software developers, DevOps teams, and other stakeholders to deliver reliable data solutions.
Troubleshoot production issues and support the continuous improvement of data engineering processes.

Requirements:

Bachelor’s degree in computer science or Diploma in IT with equivalent experience.

Python and Data Processing

Advanced proficiency in Python.
Strong experience with pandas and Polars for data manipulation, transformation, and analysis.
Experience working with large datasets and optimizing code for performance and memory usage.
Strong understanding of Python development best practices, object-oriented programming, and clean code principles.

Containerization and Orchestration

Hands-on experience building and managing container images using Docker.
Experience creating and maintaining multi-container applications.
Working knowledge of Kubernetes for container orchestration, deployment, scaling, and service management.

Data Infrastructure

Experience with ClickHouse or a similar columnar database.
Understanding of OLAP workloads, analytical queries, data modeling, and query optimization.
Experience designing data pipelines for analytical and reporting use cases.

Messaging and Streaming

Familiarity with NATS.io and message-driven architectures.
Understanding of asynchronous processing, event-driven systems, messaging patterns, and distributed workflows.

Testing and Quality Assurance

Proficiency with pytest.
Experience writing unit tests, integration tests, and regression tests.
Understanding of test coverage, mocking, test automation, and quality assurance practices.

Distributed Computing

Experience with Dask for parallel processing and out-of-core computation.
Understanding of distributed data processing and techniques for handling datasets that exceed available system memory.

Version Control

Strong command of Git, including branching strategies, pull requests, code reviews, merging, and conflict resolution.
Experience collaborating through shared code repositories and following software development best practices.

Apply About employer

More about this job

Responsibilities

Develop and optimize Python-based data transformation workflows and scalable pipelines for large datasets, including distributed processing and analytical workloads. Build and deploy containerized services, implement event-driven messaging, maintain automated tests and code quality, and collaborate with engineering and DevOps teams to support reliable production data solutions.

Requirements

Requires advanced Python proficiency and strong experience with pandas and Polars, large-scale data processing, performance optimization, and clean coding practices. Candidates should also have hands-on experience with Docker, Kubernetes, columnar databases, NATS, Dask, pytest, and Git, along with a bachelor’s degree in computer science or an IT diploma with equivalent experience.

Skills

Python
Pandas
Polars
Data Engineering
Data Pipelines
Docker
Kubernetes
ClickHouse
NATS
Dask
Pytest
Git
Distributed Computing
Performance Optimization
Data Modeling
Event-Driven Architecture

Visa sponsorship

Not detected in the job text

Keywords

Python
Pandas
Polars
Data Engineering
Data Processing
Data Pipelines
Large-Scale Datasets
Performance Optimization
Memory Efficiency
Docker
Containerization
Kubernetes
ClickHouse
Columnar Databases
OLAP
Data Modeling
Query Optimization
NATS
Event-Driven Architecture
Asynchronous Processing
Dask
Distributed Computing
Out-of-Core Computation
Pytest
Unit Testing
Integration Testing
Regression Testing
Git
Code Reviews
Object-Oriented Programming

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