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

Salary details

The average mid-level / intermediate Data Manager salary lies between USD 70,000 and USD 110,000 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 Data Manager roles

The three most common job tag items assiciated with mid-level / intermediate Data Manager job listings are Data management, Data quality and Excel. 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:

Data management | 438 jobs Data quality | 227 jobs Excel | 219 jobs Research | 216 jobs SQL | 202 jobs Security | 176 jobs Engineering | 145 jobs Data governance | 128 jobs Statistics | 114 jobs Data analysis | 114 jobs Computer Science | 113 jobs Python | 106 jobs R | 105 jobs Power BI | 102 jobs Pharma | 98 jobs Testing | 95 jobs Architecture | 84 jobs Privacy | 81 jobs Finance | 79 jobs Data Analytics | 73 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate Data Manager 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 | 358 jobs Health care | 223 jobs Flex hours | 183 jobs Team events | 120 jobs Competitive pay | 113 jobs Insurance | 100 jobs Startup environment | 99 jobs Equity / stock options | 92 jobs Salary bonus | 83 jobs Flex vacation | 60 jobs Medical leave | 47 jobs Parental leave | 46 jobs Wellness | 41 jobs 401(k) matching | 29 jobs Conferences | 21 jobs Relocation support | 17 jobs Gear | 15 jobs Home office stipend | 15 jobs Yoga | 14 jobs Transparency | 12 jobs

Salary Composition

In Canada, the salary composition for a Mid-level/Intermediate Data Manager in AI/ML/Data Science typically includes a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or benefits. The fixed base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Bonuses can vary significantly depending on the company and industry, often comprising 10% to 20% of the total salary. Additional remuneration, such as stock options, profit-sharing, or comprehensive benefits packages, can make up the remaining 5% to 10%.

Regional differences can also impact salary composition. For instance, tech hubs like Toronto or Vancouver might offer higher base salaries and more lucrative stock options due to the competitive job market. Industry-wise, tech companies and financial institutions tend to offer more substantial bonuses and stock options compared to smaller startups or non-tech industries. Larger companies often provide more comprehensive benefits and additional perks, which can enhance the overall compensation package.

Increasing Salary

To increase your salary from a Mid-level/Intermediate Data Manager position, consider the following strategies:

• Skill Enhancement: Continuously update your skills in emerging AI/ML technologies and tools. Specializing in high-demand areas like deep learning, natural language processing, or big data analytics can make you more valuable.

• Advanced Education: Pursuing further education, such as a master's degree or specialized certifications, can position you for higher-paying roles.

• Networking: Engage with industry professionals through conferences, workshops, and online platforms. Networking can open doors to new opportunities and provide insights into higher-paying roles.

• Leadership Roles: Seek opportunities to lead projects or teams. Demonstrating leadership skills can position you for promotions to senior management roles, which typically offer higher salaries.

• Negotiation Skills: Improve your negotiation skills to effectively advocate for higher pay during performance reviews or when considering new job offers.

Educational Requirements

For a Mid-level/Intermediate Data Manager role, a bachelor's degree in a relevant field such as Computer Science, Data Science, Statistics, or Information Technology is typically required. Some employers may prefer candidates with a master's degree, especially in competitive markets or for roles with more complex responsibilities. A strong foundation in mathematics, statistics, and programming is essential, as these skills are crucial for data analysis and model development.

Helpful Certifications

Certifications can enhance your qualifications and demonstrate expertise in specific areas. Some valuable certifications for this role include:

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Microsoft Certified: Azure Data Scientist Associate: Demonstrates proficiency in using Azure for data science solutions.
• Google Professional Data Engineer: Focuses on designing and building data processing systems on Google Cloud.
• AWS Certified Machine Learning – Specialty: Highlights expertise in building, training, and deploying ML models on AWS.

Experience Requirements

Typically, a Mid-level/Intermediate Data Manager position requires 3 to 5 years of experience in data management, analysis, or a related field. Experience with data modeling, database management, and data visualization tools is often necessary. Familiarity with programming languages such as Python, R, or SQL is also commonly required. Experience in leading projects or teams can be advantageous, as it demonstrates your ability to manage and coordinate complex data initiatives.

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