Salary for Mid-level / Intermediate Data Engineer in Canada during 2023

Salary details

The average mid-level / intermediate Data Engineer salary lies between USD 99,000 and USD 190,000 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

Salary trend

Top 20 Job Tags for Mid-level / Intermediate Data Engineer roles

The three most common job tag items assiciated with mid-level / intermediate Data Engineer job listings are Python, SQL and Engineering. 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 | 1005 jobs SQL | 983 jobs Engineering | 967 jobs Pipelines | 885 jobs AWS | 673 jobs Data pipelines | 673 jobs ETL | 638 jobs Computer Science | 565 jobs Architecture | 527 jobs Spark | 520 jobs Azure | 508 jobs Agile | 449 jobs Machine Learning | 385 jobs GCP | 363 jobs Big Data | 359 jobs Security | 339 jobs Data quality | 329 jobs Airflow | 324 jobs Data warehouse | 311 jobs Java | 311 jobs

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

The three most common job benefits and perks assiciated with mid-level / intermediate 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 | 779 jobs Health care | 462 jobs Flex hours | 416 jobs Startup environment | 374 jobs Team events | 302 jobs Competitive pay | 274 jobs Flex vacation | 260 jobs Parental leave | 217 jobs Equity / stock options | 166 jobs Salary bonus | 161 jobs Insurance | 153 jobs Medical leave | 109 jobs Wellness | 93 jobs 401(k) matching | 92 jobs Home office stipend | 79 jobs Gear | 78 jobs Conferences | 52 jobs Unlimited paid time off | 51 jobs Fitness / gym | 50 jobs Yoga | 32 jobs

Salary Composition

In Canada, the salary composition for a mid-level/intermediate data engineer in AI/ML/Data Science typically includes a base salary, performance bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company's profitability and individual performance metrics. Additional remuneration might include stock options, especially in tech companies or startups, and comprehensive benefits packages that cover health, dental, and retirement plans. The composition can vary by region, with tech hubs like Toronto and Vancouver offering higher base salaries but potentially lower bonuses compared to smaller cities. Industry also plays a role; for instance, finance and tech sectors might offer higher bonuses compared to academia or public sector roles. Company size can influence stock options and benefits, with larger companies often providing more comprehensive packages.

Increasing Salary

To increase your salary from a mid-level data engineer position, consider the following strategies:

• Skill Enhancement: Continuously update your technical skills, especially in emerging technologies like cloud computing, big data frameworks, and machine learning algorithms.
• Advanced Education: Pursue advanced degrees or specialized certifications that can make you more competitive.
• Networking: Engage with professional networks and communities to learn about new opportunities and industry trends.
• Leadership Roles: Aim for roles that offer leadership responsibilities, such as team lead or project manager, which often come with higher pay.
• Industry Switch: Consider moving to industries that pay higher salaries for data engineering roles, such as finance or tech.

Educational Requirements

Most mid-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 can be advantageous and is often preferred by employers, especially for roles that involve complex data modeling and machine learning tasks. Some positions might also value interdisciplinary degrees that combine technical skills with business acumen.

Helpful Certifications

Certifications can enhance your profile and demonstrate your expertise in specific areas. Some valuable certifications for data engineers include:

• Google Professional Data Engineer
• AWS Certified Data Analytics – Specialty
• Microsoft Certified: Azure Data Engineer Associate
• Cloudera Certified Professional (CCP) Data Engineer

These certifications validate your skills in cloud platforms and data engineering tools, making you more attractive to potential employers.

Required Experience

Typically, a mid-level data engineer is expected to have 3-5 years of experience in data engineering or related fields. This experience should include hands-on work with data pipelines, ETL processes, and data warehousing solutions. Experience with cloud platforms like AWS, Azure, or Google Cloud is often required, as well as proficiency in programming languages such as Python, Java, or Scala.

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