DevOps Engineer Salary in Canada during 2024

Salary details

The average DevOps Engineer salary lies between USD 98,600 and USD 144,650 in Canada. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 10, 2024

Top 20 Job Tags for DevOps Engineer roles

The three most common job tag items assiciated with DevOps Engineer job listings are DevOps, Python and Kubernetes. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

DevOps | 529 jobs Python | 481 jobs Kubernetes | 391 jobs Engineering | 381 jobs AWS | 377 jobs CI/CD | 372 jobs Security | 339 jobs Pipelines | 330 jobs Terraform | 321 jobs Machine Learning | 289 jobs Docker | 288 jobs Linux | 251 jobs Azure | 240 jobs Computer Science | 231 jobs Ansible | 230 jobs Jenkins | 210 jobs Architecture | 206 jobs GCP | 180 jobs Agile | 177 jobs Git | 164 jobs

Top 20 Job Perks/Benefits for DevOps Engineer roles

The three most common job benefits and perks assiciated with DevOps Engineer job listings are Career development, Flex hours and Health care. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 377 jobs Flex hours | 198 jobs Health care | 170 jobs Startup environment | 142 jobs Team events | 119 jobs Competitive pay | 113 jobs Equity / stock options | 101 jobs Flex vacation | 97 jobs Salary bonus | 65 jobs Insurance | 62 jobs Medical leave | 59 jobs Parental leave | 39 jobs Gear | 36 jobs 401(k) matching | 31 jobs Wellness | 27 jobs Home office stipend | 24 jobs Conferences | 18 jobs Transparency | 17 jobs Pet friendly | 17 jobs Flexible spending account | 17 jobs

Salary Composition

In Canada, the salary composition for a DevOps Engineer specializing in AI/ML/Data Science can vary significantly based on factors such as region, industry, and company size. Typically, the salary is divided into three main components:

• Base Salary: This is the fixed annual amount and usually constitutes the largest portion of the total compensation. In major tech hubs like Toronto or Vancouver, the base salary might be higher due to the cost of living and demand for tech talent.

• Bonus: Many companies offer performance-based bonuses, which can range from 5% to 20% of the base salary. The bonus structure often depends on the company's performance, individual performance, and sometimes team performance.

• Additional Remuneration: This can include stock options, profit-sharing, or other incentives. Larger tech companies or startups might offer equity as part of the compensation package, which can be a significant financial benefit if the company performs well.

Increasing Salary

To increase your salary further from this position, consider the following steps:

• Skill Enhancement: Continuously update your skills in AI/ML and DevOps. Specializing in emerging technologies or tools can make you more valuable.

• Advanced Certifications: Obtaining advanced certifications in AI/ML or cloud platforms can enhance your profile and justify a higher salary.

• Networking: Engage with professional networks and communities. Building relationships with industry leaders can open up opportunities for higher-paying roles.

• Leadership Roles: Transitioning into a leadership or managerial role can significantly increase your earning potential. This might involve leading a team of DevOps engineers or managing cross-functional projects.

Educational Requirements

For a DevOps Engineer role in AI/ML/Data Science, the most common educational requirements include:

• Bachelor’s Degree: Typically in Computer Science, Software Engineering, or a related field. This provides a strong foundation in programming and systems design.

• Master’s Degree: While not always required, a master’s degree in Data Science, AI, or a related field can be advantageous and may lead to higher starting salaries.

Helpful Certifications

Certifications can bolster your credentials and demonstrate expertise. Some valuable certifications include:

• AWS Certified DevOps Engineer: Demonstrates proficiency in deploying, operating, and managing distributed application systems on the AWS platform.

• Google Professional Data Engineer: Validates your ability to design, build, and operationalize data processing systems.

• Certified Kubernetes Administrator (CKA): Useful for managing containerized applications, which is often a part of DevOps roles.

Required Experience

The usual experience required for a DevOps Engineer in AI/ML/Data Science includes:

• 3-5 Years in DevOps: Experience with CI/CD pipelines, cloud services, and infrastructure as code.

• Experience with AI/ML Tools: Familiarity with AI/ML frameworks and tools such as TensorFlow, PyTorch, or Scikit-learn.

• Project Experience: Hands-on experience with deploying AI/ML models in production environments.

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