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Python Automation Testing Jobs in Ontario (NOW HIRING)

Write Python, bash, and CI/CD automation that reduces manual toil, improves reliability, and makes ... Comfortable using Git-based development workflows, pull requests, automated testing, and CI/CD ...

Automation Analyst

Toronto, ON ยท On-site

$90 - $118/hr

Lead development, testing, and lifecycle management of automated processes that leverage Microsoft ... Experience programming with a language such as Python, Java, Go, C, or developing applications with ...

Lead the development, testing, and lifecycle management of automated processes that leverage ... Experience programming with a language such as Python, Java, Go, C, or developing applications with ...

Showing results 41-60

Python Automation Testing information

What is the difference between Python Automation Testing vs Manual Software Testing?

AspectPython Automation TestingManual Software Testing
Required SkillsPython programming, automation tools, scriptingTest case execution, attention to detail, communication
Work EnvironmentAutomated testing frameworks, scripting environmentsTest labs, user environments, manual execution
Industry UsageSoftware development, QA teams, continuous integrationInitial testing phases, exploratory testing, user acceptance

Python Automation Testing involves writing scripts to automate test cases, increasing efficiency and repeatability. Manual Software Testing requires testers to execute test cases manually, focusing on exploratory and usability aspects. Both roles are essential in software quality assurance, but Python Automation Testing emphasizes automation skills, while manual testing emphasizes detailed test execution and observation.

What are the key skills and qualifications needed for Python automation testing?

To thrive as a Python Automation Testing professional, you need strong proficiency in Python programming, knowledge of software testing methodologies, and experience with test automation frameworks, often supported by a degree in computer science or a related field. Familiarity with tools such as Selenium, PyTest, Jenkins, and version control systems like Git is typically required, along with certifications like ISTQB being advantageous. Analytical thinking, attention to detail, and effective communication skills help testers identify issues, collaborate with teams, and document findings clearly. These competencies ensure the creation of reliable, maintainable automated tests that improve software quality and streamline development cycles.

What are common challenges in Python automation testing, and how can they be addressed?

One common challenge in Python Automation Testing is maintaining test scripts as applications evolve, which can lead to flaky tests or outdated scripts. To address this, it's important to implement modular and reusable code, and regularly review and refactor test cases. Collaborating closely with developers and participating in code reviews can also help testers anticipate changes and adapt their tests proactively. Additionally, integrating robust reporting and logging mechanisms helps quickly identify and resolve issues, ensuring the reliability of the automated test suite.

What is Python automation testing?

Python Automation Testing refers to the process of using Python programming language to write scripts that automatically test software applications. These scripts can validate functionality, performance, and reliability of software, reducing the need for manual testing and speeding up the development cycle. Python is popular for automation testing because of its readability, extensive libraries like Selenium and PyTest, and strong community support. Automation tests can be integrated into continuous integration pipelines to ensure consistent quality across software releases.
What are popular job titles related to Python Automation Testing jobs in Ontario? For Python Automation Testing jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Python Automation Testing jobs in Ontario look for? The top searched job categories for Python Automation Testing jobs in Ontario are:
What cities in Ontario are hiring for Python Automation Testing jobs? Cities in Ontario with the most Python Automation Testing job openings:
Infographic showing various Python Automation Testing job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 10% Part Time, 4% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Data Platform Engineer

Tucows

Toronto, ON โ€ข Remote

Full-time

Posted 29 days ago


Job description

Tucows (NASDAQ:TCX, TSX:TC) is possibly the biggest Internet company you've never heard of. We started as a simple shareware site in 1993 and have since grown into a stable of businesses: Tucows Domains, Ting Internet and Wavelo.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It's also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet!

Today, over one thousand people work in over 20 countries to help us make the Internet better. If this sounds exciting to you, join the herd!

About the Role

We're looking for a curious, technically strong, and automation-minded Data Platform Engineer to join our Data Engineering team. This is a high-impact platform engineering role for someone who enjoys building reliable systems, writing maintainable automation, and helping data teams move faster, more safely, and with more confidence.

You'll work at the intersection of data engineering, business intelligence, finance analytics, cloud infrastructure, governance, and AI-enabled decision support. What we're really hiring for is strong engineering fundamentals, comfort with ambiguity, and the drive to apply those fundamentals across different systems.

We're hiring an engineer who can pick up infrastructure work, governance work, or pipeline work as needed and help turn knowledge that currently lives in repos, configs, and people's heads into durable platform practices. There will be a lot to learn here, even if you arrive experienced. That's the appeal, not the catch.

What You'll Do

Keep the data platform healthy: Monitor infrastructure and pipelines, respond to issues, troubleshoot failures from logs and metrics, and help identify root causes so we can prevent repeat problems.

Make infrastructure changes safely: Build, review, and deploy infrastructure through code using Terraform, AWS, Kubernetes or container-based deployment patterns, and CI/CD workflows.

Improve automation and tooling: Write Python, bash, and CI/CD automation that reduces manual toil, improves reliability, and makes common platform tasks safer and easier for the team.

Support access control and governance: Help design and operate role-based access control, least-privilege access, and governance controls across our cloud, warehouse, and BI platforms.

Contribute to data pipelines: Build, operate, and troubleshoot pipelines and transformations that power reporting, analytics, finance workflows, and data products across the company.

Support our platform migration: Help move workloads from our legacy stack to the modern data platform, including validation, cutover, and decommissioning work.

Document how things work: Write clear runbooks, platform documentation, and operational guides so knowledge is easier to share and the team is less dependent on any one person.

Use and improve AI-assisted engineering: Work with our Claude Code-based tooling, including agents, skills, hooks, and MCP integrations, and help shape how the team uses AI to improve engineering workflows.

What We're Looking For

Experience: 3+ years in data engineering, software engineering, DevOps, platform engineering, or a related technical role.

Cloud and DevOps fundamentals: Hands-on experience operating workloads in AWS or another major cloud provider, with a solid grasp of IAM, networking, compute, managed services, deployment patterns, and day-to-day cloud operations.

Python automation: Proficiency in Python for automation, internal tooling, platform workflows, or data engineering support.

SQL competency: Working knowledge of SQL. Advanced SQL is a plus, but not a prerequisite.

Infrastructure as Code: Hands-on experience with Terraform or another infrastructure-as-code tool, including code review, state-aware changes, environment management, and safe deployment practices.

CI/CD and Git workflows: Comfortable using Git-based development workflows, pull requests, automated testing, and CI/CD pipelines to ship changes safely.

Kubernetes and containerized workloads: Good working knowledge of Kubernetes and container-based deployments. You should be comfortable understanding deployments, pods, services, logs, configuration, and common failure modes. Experience with EKS is especially valuable.

Observability, Debugging and Operations: Skilled at using logs, metrics, and alerts to investigate failing systems, reason through incomplete information, and identify likely root causes.

Access control and governance mindset: Familiarity with RBAC, IAM, least-privilege access, or governance controls in at least one platform — cloud, warehouse, BI, or application-level systems.

Strong fundamentals and learning mindset: Attention to detail, curiosity, good judgment, and genuine eagerness to learn unfamiliar tools and systems.

Vendor & Incident Management: Experience working with vendor support, production incidents, severity-based escalation, and operational follow-through.

Operational Ownership: Willingness to participate in on-call and after-hours support as needed. You understand that reliable platforms require thoughtful operations, not just build work.

Remote collaboration: Clear written communication and the ability to work effectively with engineers, analysts, and data stakeholders in a remote-first team.

Our Broader Stack

Cloud & Infrastructure: AWS, GCP, OpenStack, Terraform, Docker, Kubernetes, Helm
Data Platform: Snowflake, BigQuery, dbt, Airflow/MWAA, Kafka, DataHub
Ingestion & Legacy Systems: Fivetran, Stitch, Pentaho Data Integration
Observability: Prometheus, Grafana, CloudWatch
BI & Development Workflow: Looker, GitHub, Claude Code

​​The base salary range for this position is $90,700 - $113,400. Range shown in $CAD for Canadian residents. Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous bene

Experience with these tools is a plus, what matters most is that you bring strong engineering fundamentals, sound operational judgment, and the ability to learn quickly.

Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing the digital divide, and supporting fairness and equality.

We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

We use AI-enabled tools throughout our recruitment process to help us work more efficiently and consistently. These tools support our hiring teams by organizing and reviewing information, while final hiring decisions are always made by people.

Tucows and its subsidiaries participate in the E-verify program for all US employees.

Learn more about Tucows, our businesses, culture and employee benefits on our site here.