Salary for Senior-level / Expert Data Engineer in Canada during 2023

Salary details

The average senior-level / expert Data Engineer salary lies between USD 95,000 and USD 160,000 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: Dec. 15, 2024

Salary trend

Top 20 Job Tags for Senior-level / Expert Data Engineer roles

The three most common job tag items assiciated with senior-level / expert Data Engineer job listings are Python, Engineering and SQL. Below you find a list of the 20 most occuring job tags in 2023 and the number of open jobs that where associated with them during that period:

Python | 3304 jobs Engineering | 3209 jobs SQL | 3062 jobs Pipelines | 2762 jobs AWS | 2324 jobs Spark | 2201 jobs Architecture | 2187 jobs Data pipelines | 2051 jobs ETL | 1996 jobs Big Data | 1735 jobs Computer Science | 1696 jobs Agile | 1650 jobs Java | 1525 jobs Azure | 1447 jobs Airflow | 1335 jobs Kafka | 1274 jobs Machine Learning | 1263 jobs Security | 1223 jobs Scala | 1184 jobs GCP | 1177 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Data Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert 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 2023 and the number of open jobs that where offering them during that period:

Career development | 2566 jobs Health care | 1375 jobs Flex hours | 1294 jobs Startup environment | 1121 jobs Team events | 915 jobs Flex vacation | 861 jobs Competitive pay | 821 jobs Equity / stock options | 780 jobs Parental leave | 706 jobs Salary bonus | 703 jobs Insurance | 688 jobs Medical leave | 506 jobs Wellness | 482 jobs 401(k) matching | 358 jobs Home office stipend | 246 jobs Fitness / gym | 195 jobs Unlimited paid time off | 184 jobs Gear | 141 jobs Conferences | 116 jobs Relocation support | 103 jobs

Salary Composition

In Canada, the salary composition for a Senior-level or Expert Data Engineer in AI/ML/Data Science typically includes a mix of base salary, bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is often the largest component, accounting for approximately 70-80% of the total compensation package. Bonuses can vary significantly depending on the company and industry, ranging from 10-20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can make up 5-15% of the total package. Regional differences also play a role; for instance, salaries in major tech hubs like Toronto or Vancouver might be higher compared to other regions. Industry-wise, tech companies and financial services tend to offer more competitive packages compared to other sectors.

Increasing Salary Further

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

• Specialization: Develop expertise in niche areas of data engineering, such as big data technologies, cloud computing, or machine learning infrastructure, which are in high demand.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Engineering Manager or Director of Data Engineering, which typically come with higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML and data engineering. This could involve taking advanced courses or certifications.
• Networking: Engage with professional networks and communities. This can open up opportunities for higher-paying roles and provide insights into industry trends.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements

Most senior-level data engineering positions require at least a bachelor's degree in computer science, engineering, mathematics, or a related field. However, a master's degree or even a Ph.D. can be advantageous, especially for roles that require a deep understanding of machine learning or data science. Advanced degrees can also help differentiate candidates in a competitive job market.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

• Certified Data Management Professional (CDMP)
• Google Cloud Professional Data Engineer
• AWS Certified Big Data – Specialty
• Microsoft Certified: Azure Data Engineer Associate
• Cloudera Certified Professional (CCP) Data Engineer

These certifications can validate your skills in specific technologies and platforms, making you more attractive to potential employers.

Required Experience

Typically, a senior-level data engineer is expected to have 5-10 years of experience in data engineering or related fields. This experience should include a strong background in data architecture, ETL processes, data warehousing, and proficiency in programming languages such as Python, Java, or Scala. Experience with cloud platforms like AWS, Google Cloud, or Azure is also highly valued.

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