Salary for Senior-level / Expert Analytics Engineer in Canada during 2024

Salary details

The average senior-level / expert Analytics Engineer salary lies between USD 140,000 and USD 194,500 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 Senior-level / Expert Analytics Engineer roles

The three most common job tag items assiciated with senior-level / expert Analytics Engineer job listings are SQL, Engineering 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:

SQL | 815 jobs Engineering | 754 jobs Python | 675 jobs dbt | 511 jobs Pipelines | 465 jobs ETL | 381 jobs Looker | 376 jobs Snowflake | 374 jobs Tableau | 355 jobs Data quality | 340 jobs Data pipelines | 316 jobs Airflow | 310 jobs Testing | 306 jobs Data Analytics | 303 jobs AWS | 298 jobs Data warehouse | 293 jobs Computer Science | 292 jobs Architecture | 271 jobs Business Intelligence | 240 jobs Machine Learning | 225 jobs

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

The three most common job benefits and perks assiciated with senior-level / expert Analytics 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 | 617 jobs Health care | 395 jobs Flex hours | 373 jobs Equity / stock options | 317 jobs Startup environment | 317 jobs Flex vacation | 248 jobs Competitive pay | 242 jobs Team events | 217 jobs Parental leave | 212 jobs Salary bonus | 159 jobs Insurance | 144 jobs Medical leave | 136 jobs Wellness | 129 jobs 401(k) matching | 119 jobs Unlimited paid time off | 104 jobs Home office stipend | 93 jobs Fitness / gym | 76 jobs Gear | 51 jobs Transparency | 37 jobs Conferences | 37 jobs

Salary Composition for Senior-level Analytics Engineers in Canada

The salary for a Senior-level or Expert Analytics Engineer in Canada typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is often the largest component, accounting for approximately 70-80% of the total compensation package. Performance bonuses can vary significantly depending on the company and industry, ranging from 10-20% of the base salary. Additional remuneration, such as stock options, profit-sharing, or comprehensive benefits packages, can make up the remaining 5-10%.

In terms of regional differences, salaries in major tech hubs like Toronto or Vancouver might be higher due to the cost of living and demand for tech talent. Industry-wise, tech companies, especially those in AI and machine learning, tend to offer more competitive packages compared to traditional industries. Larger companies might offer more in terms of stock options and bonuses, while smaller startups might compensate with equity.

Steps to Increase Salary from a Senior-level Position

To increase your salary further from a senior-level position, consider the following strategies:

• Specialization: Develop expertise in a niche area of AI/ML or data science that is in high demand but has a limited supply of experts.
• Leadership Roles: Transition into leadership or managerial roles, such as a Director of Analytics or Chief Data Officer, which typically come with higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML. This could involve taking advanced courses or attending industry conferences.
• Networking: Build a strong professional network to learn about higher-paying opportunities and gain 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 for Senior-level Analytics Engineers

Most senior-level analytics engineering positions require at least a bachelor's degree in a relevant field such as Computer Science, Data Science, Statistics, or Engineering. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex problem-solving and advanced analytics. These advanced degrees provide a deeper understanding of machine learning algorithms, statistical methods, and data management techniques, which are crucial for high-level analytics roles.

Helpful Certifications for Analytics Engineers

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Google Professional Data Engineer: Demonstrates proficiency in designing, building, and operationalizing data processing systems.
• AWS Certified Machine Learning – Specialty: Shows expertise in building, training, and deploying machine learning models on AWS.
• Microsoft Certified: Azure Data Scientist Associate: Focuses on applying data science and machine learning techniques on Azure.

Experience Required for Senior-level Roles

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

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