Salary for Mid-level / Intermediate Engineering Manager in Canada during 2024

Salary details

The average mid-level / intermediate Engineering Manager salary lies between USD 177,300 and USD 202,000 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: Nov. 17, 2024

Top 20 Job Tags for Mid-level / Intermediate Engineering Manager roles

The three most common job tag items assiciated with mid-level / intermediate Engineering Manager job listings are Engineering, Machine Learning and Python. 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 | 601 jobs Machine Learning | 376 jobs Python | 349 jobs Computer Science | 257 jobs Architecture | 230 jobs Pipelines | 203 jobs AWS | 191 jobs Research | 161 jobs Security | 157 jobs SQL | 154 jobs Agile | 152 jobs Testing | 130 jobs Privacy | 126 jobs Java | 123 jobs Distributed Systems | 111 jobs Spark | 110 jobs Data pipelines | 109 jobs Azure | 107 jobs GCP | 102 jobs Kubernetes | 98 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Engineering Manager roles

The three most common job benefits and perks assiciated with mid-level / intermediate Engineering Manager job listings are Career development, Health care and Equity / stock options. 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 | 498 jobs Health care | 290 jobs Equity / stock options | 233 jobs Startup environment | 198 jobs Flex hours | 195 jobs Salary bonus | 179 jobs Parental leave | 157 jobs Flex vacation | 151 jobs Team events | 142 jobs Competitive pay | 123 jobs Insurance | 118 jobs Medical leave | 101 jobs 401(k) matching | 79 jobs Home office stipend | 67 jobs Wellness | 53 jobs Unlimited paid time off | 44 jobs Gear | 38 jobs Transparency | 38 jobs Relocation support | 34 jobs Conferences | 29 jobs

Salary Composition

In Canada, the salary composition for a Mid-level/Intermediate Engineering Manager 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, which can be performance-based or company-wide, usually make up about 10-20%. Additional remuneration, such as stock options, equity, or other benefits, can vary significantly depending on the company size and industry. For instance, larger tech companies or startups might offer more in terms of equity, while traditional industries might focus more on cash bonuses. Regional differences also play a role, with tech hubs like Toronto or Vancouver potentially offering higher compensation packages compared to other regions.

Increasing Salary Further

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

• Skill Enhancement: Continuously update your technical and managerial skills. Specializing in emerging AI/ML technologies or methodologies can make you more valuable.
• Networking: Build a strong professional network within the industry. Attend conferences, workshops, and meetups to connect with industry leaders and peers.
• Leadership Roles: Seek opportunities to lead larger teams or more complex projects. Demonstrating your ability to manage bigger responsibilities can justify a higher salary.
• Negotiation: When discussing salary, be prepared with market data and a clear understanding of your value to the company. Highlight your achievements and contributions.
• Advanced Education: Consider pursuing an advanced degree or executive education in business or technology management to position yourself for higher-level roles.

Educational Requirements

Most mid-level engineering manager roles in AI/ML/Data Science require at least a bachelor's degree in computer science, engineering, data science, or a related field. However, a master's degree is often preferred, especially in larger companies or more competitive markets. Degrees that combine technical expertise with business acumen, such as an MBA with a focus on technology management, can also be advantageous.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your commitment to the field. Some valuable certifications include:

• Certified Data Scientist (CDS)
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Microsoft Certified: Azure AI Engineer Associate
• Project Management Professional (PMP) for those focusing on managerial aspects

These certifications can help validate your skills and knowledge, making you a more attractive candidate for higher-level positions.

Required Experience

Typically, a mid-level engineering manager in AI/ML/Data Science is expected to have 5-10 years of experience in the field. This includes hands-on experience with AI/ML technologies, data analysis, and software development. Additionally, candidates should have a proven track record of leading teams, managing projects, and delivering successful outcomes. Experience in a specific industry, such as finance, healthcare, or technology, can also be beneficial.

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