Salary for Senior-level / Expert Data Developer in Canada during 2024

Salary details

The average senior-level / expert Data Developer salary lies between USD 84,000 and USD 121,000 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. 22, 2024

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

The three most common job tag items assiciated with senior-level / expert Data Developer job listings are SQL, Python and Pipelines. 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:

SQL | 164 jobs Python | 134 jobs Pipelines | 121 jobs Engineering | 110 jobs ETL | 100 jobs Spark | 95 jobs Azure | 81 jobs AWS | 78 jobs Architecture | 72 jobs Data pipelines | 69 jobs Big Data | 67 jobs Data quality | 65 jobs Security | 56 jobs Databricks | 55 jobs CI/CD | 55 jobs Agile | 53 jobs Data warehouse | 53 jobs Testing | 50 jobs Research | 48 jobs Computer Science | 47 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Data Developer job listings are Career development, Fitness / gym 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 | 117 jobs Fitness / gym | 72 jobs Health care | 71 jobs Flex hours | 39 jobs Parental leave | 27 jobs Competitive pay | 27 jobs Team events | 26 jobs Equity / stock options | 22 jobs Startup environment | 19 jobs Flex vacation | 16 jobs Wellness | 15 jobs Insurance | 14 jobs Transparency | 11 jobs Medical leave | 9 jobs Relocation support | 7 jobs Salary bonus | 6 jobs Home office stipend | 5 jobs Conferences | 3 jobs Lunch / meals | 2 jobs Travel | 2 jobs

Salary Composition

In Canada, the salary composition for a Senior-level or Expert Data Developer in AI/ML/Data Science typically includes a mix of base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is often the largest component, making up about 70-80% of the total compensation package. Bonuses, which can be performance-based or company-wide, usually account for 10-20%. Additional remuneration, such as stock options, profit-sharing, or other benefits, can make up the remaining 5-10%. The exact composition can vary significantly depending on the region, industry, and company size. For instance, tech companies in major cities like Toronto or Vancouver might offer more in terms of stock options, while companies in smaller regions might focus more on base salary.

Increasing Salary

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

• Skill Enhancement: Continuously update your skills in emerging technologies and tools in AI/ML. Specializing in niche areas like deep learning, natural language processing, or computer vision can make you more valuable.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Science Manager or Director of Data Science, which typically offer higher salaries.
• Networking: Engage with professional networks and communities. Attending conferences, workshops, and meetups can open up opportunities for higher-paying roles.
• Industry Switch: Consider switching to industries that pay more for data expertise, such as finance, healthcare, or tech startups.
• Negotiation: Improve your negotiation skills to better advocate for higher pay during performance reviews or when switching jobs.

Educational Requirements

Most senior-level positions in AI/ML/Data Science require at least a bachelor's degree in a related field such as Computer Science, Mathematics, Statistics, or Engineering. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex problem-solving and research. Advanced degrees can provide a deeper understanding of machine learning algorithms, data analysis, and statistical modeling, which are crucial for high-level positions.

Helpful Certificates

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

• Certified Data Scientist (CDS)
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• AWS Certified Machine Learning – Specialty
• TensorFlow Developer Certificate

These certifications can validate your skills and knowledge, making you more competitive in the job market.

Required Experience

Typically, a senior-level position requires 5-10 years of experience in data science or a related field. This experience should include hands-on work with data analysis, machine learning model development, and deployment. Experience in leading projects, mentoring junior team members, and collaborating with cross-functional teams is also highly valued.

Related salaries

Want to contribute?