Data Engineer Salary in Canada during 2024

Salary details

The average Data Engineer salary lies between USD 92,190 and USD 166,000 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: Feb. 16, 2025

Salary trend

Top 20 Job Tags for Data Engineer roles

The three most common job tag items assiciated with Data Engineer job listings are Engineering, Python and SQL. 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:

Engineering | 15568 jobs Python | 15072 jobs SQL | 14951 jobs Pipelines | 13057 jobs ETL | 10344 jobs Data pipelines | 9885 jobs AWS | 9760 jobs Architecture | 8910 jobs Computer Science | 8719 jobs Spark | 8530 jobs Azure | 7606 jobs Big Data | 7312 jobs Agile | 6779 jobs Security | 6699 jobs Machine Learning | 6088 jobs Data quality | 5677 jobs Java | 5597 jobs GCP | 5264 jobs Airflow | 4964 jobs Snowflake | 4909 jobs

Top 20 Job Perks/Benefits for Data Engineer roles

The three most common job benefits and perks assiciated with Data Engineer job listings are Career development, Health care and Flex hours. 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 | 12105 jobs Health care | 6289 jobs Flex hours | 5123 jobs Team events | 3669 jobs Startup environment | 3629 jobs Competitive pay | 3477 jobs Equity / stock options | 3281 jobs Flex vacation | 2807 jobs Salary bonus | 2765 jobs Insurance | 2672 jobs Parental leave | 2473 jobs Medical leave | 2225 jobs Wellness | 1669 jobs 401(k) matching | 1402 jobs Fitness / gym | 758 jobs Transparency | 562 jobs Gear | 561 jobs Home office stipend | 557 jobs Relocation support | 550 jobs Unlimited paid time off | 453 jobs

Salary Composition

In Canada, the salary composition for a Data Engineer in the AI/ML/Data Science field can vary significantly based on factors such as region, industry, and company size. Typically, the salary is composed of a fixed base salary, which forms the bulk of the compensation package. This base salary can range from 70% to 90% of the total compensation. Bonuses are also a common component, often tied to individual performance, company performance, or both. These bonuses can account for 10% to 20% of the total salary. Additionally, some companies offer stock options or equity, especially in tech startups or larger tech firms, which can add a significant amount to the overall compensation package. Benefits such as health insurance, retirement contributions, and other perks can also be part of the remuneration, though they are not typically included in the salary index figures.

Increasing Salary

To increase your salary further from a Data Engineer position, consider the following steps:

• Skill Enhancement: Continuously update and expand your technical skills, particularly in emerging technologies and tools relevant to data engineering.
• Advanced Education: Pursue advanced degrees or specialized certifications that can set you apart from your peers.
• Leadership Roles: Aim for leadership or managerial roles within your team or organization, which often come with higher pay.
• Industry Transition: Consider moving to industries that pay higher salaries for data engineering roles, such as finance or tech.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain insights into salary trends.

Educational Requirements

Most Data Engineer positions require at least a bachelor's degree in a related field such as Computer Science, Information Technology, or Engineering. However, a master's degree can be advantageous and is often preferred by employers, especially for roles in AI/ML/Data Science. Degrees in Data Science or specialized programs focusing on data engineering can also be beneficial.

Helpful Certifications

Certifications can enhance your credentials and demonstrate your expertise to potential employers. Some common and helpful certifications for Data Engineers include:

• Google Professional Data Engineer
• AWS Certified Data Analytics – Specialty
• Microsoft Certified: Azure Data Engineer Associate
• Cloudera Certified Professional (CCP) Data Engineer

These certifications validate your skills in specific platforms and tools, making you a more attractive candidate for employers.

Experience Requirements

Typically, employers look for candidates with at least 2-5 years of experience in data engineering or related fields. Experience with data modeling, ETL processes, data warehousing, and big data technologies is often required. Experience in AI/ML projects can also be a significant advantage, as it demonstrates your ability to work with complex data systems and algorithms.

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