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Analytics Engineer Jobs in Ontario (NOW HIRING)

Analytics Engineer

Toronto, ON ยท On-site

CA$65K - CA$85K/yr

As an Analytics Engineer , reporting to the Director, Business Analytics Engineering , you'll be part of a centralized BAE team that supports all departments including Operations, Marketing ...

Analytics engineering is a core and growing investment, and this role sits at the center of that work. The Staff Analytics Engineer is a deeply technical individual contributor who owns the ...

The role We are looking for a Staff Analytics Engineer to lead the development of Passage's analytics foundation and decision infrastructure. This role sits at the intersection of engineering ...

If so, we want to talk to you! We're looking for a technical leader in our team to work closely with Data Scientists, Product Analysts and Software Engineers to support product launches and roadmaps ...

Strong prompt engineering skills and demonstrated ability to effectively leverage AI tools. * Proven ability to independently manage end-to-end analytical projects from problem definition through ...

You work directly with the Director of Revenue Operations & Analytics and alongside Analytics Engineers, and senior business stakeholders, and you can make sense to all of them. If you know Snowflake ...

The Engineering team is driving multiple complex, enterprise-wide initiatives to build RBC's next ... Drive deep-dive analyses on customer behavior, product performance, campaign outcomes, and channel ...

Data Engineer - Analytics Platform

Kitchener, ON ยท On-site

CA$129K - CA$178K/yr

Product Engineering, Data Science, Product Management, Strategy, Analytics, Finance, etc. Enabling these functions to do their best work without concern about underlying infrastructure. We enable ...

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Analytics Engineer information

See Ontario salary details

$62.5K

$109.1K

$178K

How much do analytics engineer jobs pay per year?

As of Jul 16, 2026, the average yearly pay for analytics engineer in Ontario is $109,135.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,500.00 and $122,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Analytics Engineer, and why are they important?

To thrive as an Analytics Engineer, you need a strong foundation in data modeling, SQL, and analytics engineering principles, often supported by a degree in computer science, data science, or a related field. Proficiency with data transformation tools such as dbt, cloud data warehouses like Snowflake or BigQuery, and version control systems like Git is essential. Strong problem-solving skills, communication, and collaboration abilities help translate business needs into scalable data solutions and foster teamwork. These skills and qualities are crucial for ensuring data quality, building reliable analytics infrastructure, and enabling data-driven decision-making across organizations.

What is the difference between Analytics Engineer vs Data Engineer?

AspectAnalytics EngineerData Engineer
CredentialsOften requires SQL, Python, data modeling certificationsRequires similar skills, often with additional focus on infrastructure and systems
Work EnvironmentFocuses on data analysis, visualization, and reportingBuilds data pipelines, manages data infrastructure
Industry UsageCommon in analytics teams, BI, and data-driven rolesPrevalent in data engineering, data platform teams

While both roles work closely with data, Analytics Engineers primarily focus on transforming data for analysis and visualization, whereas Data Engineers build the infrastructure and pipelines that enable data access. Understanding these differences helps in choosing the right career path or job role.

How does an Analytics Engineer typically collaborate with data scientists and business stakeholders on projects?

Analytics Engineers play a critical bridge role between data engineering and data analysis. They work closely with data scientists to transform raw data into clean, reliable datasets that are ready for advanced analytics or modeling. At the same time, they collaborate with business stakeholders to understand reporting needs, ensuring that data models align with business goals. Regular communication and iterative feedback are key, as Analytics Engineers often gather requirements, build data pipelines, and adjust data products based on stakeholder input.

What is an Analytics Engineer?

An Analytics Engineer is a professional who bridges the gap between data engineering and data analysis. They are responsible for designing, building, and maintaining data models, pipelines, and analytics tools that enable organizations to make data-driven decisions. Analytics Engineers often work closely with data analysts and business stakeholders to ensure clean, reliable, and well-structured data is available for reporting and analysis. Their work typically involves using SQL, data transformation tools like dbt, and cloud data warehouses to create scalable and efficient data solutions.
What are the most commonly searched types of Analytics Engineer jobs in Ontario? The most popular types of Analytics Engineer jobs in Ontario are:
What are popular job titles related to Analytics Engineer jobs in Ontario? For Analytics Engineer jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Analytics Engineer jobs in Ontario look for? The top searched job categories for Analytics Engineer jobs in Ontario are:
Infographic showing various Analytics Engineer job openings in Ontario as of July 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 79% In-person, and 21% Remote job distribution, with an average salary of $109,135 per year, or $52.5 per hour.

Analytics Engineer

Propel Holdings

Toronto, ON โ€ข On-site

CA$65K - CA$85K/yr

Full-time

Medical, Dental, PTO

Posted yesterday


Job description

About Us:

Propel (TSX: PRL) is the fintech company building a new world of financial opportunity by facilitating access to credit for consumers underserved by traditional financial institutions. Through its AI-driven platform, Propel evaluates customers in a more comprehensive way than traditional credit scores can. Our revolutionary fintech platform has already helped consumers access over one million loans and lines of credit and over one billion dollars in credit.

To build a new world of opportunity we bring together the brightest talent to help us build opportunities. We are entrepreneurs and believe in measuring success through results and growing within; talent and hard work never goes unnoticed. At Propel, we are here to change the way employees, customers and shareholders succeed together.

We are a team of passionate entrepreneurs, who foster curiosity and growth in our employees. Our culture is why we have been so successful and why our employees choose Propel to build their careers. It is also why we are one of North Americaโ€™s fastest growing companies and a Best Place to Work.

Join us as we change the way employees, customers and shareholders succeed together.

ย 

About You:

You thrive in a vibrant, entrepreneurial organization where your ideas are valued. You are motivated by goals, a self-starter, and enjoy wearing multiple hats in a fast-growing fintech environment.

As anย Analytics Engineer, reporting to theย Director, Businessย Analytics Engineering,ย youโ€™llย be part of a centralized BAEย team that supports all departments including Operations, Marketing, Compliance, Finance, and Risk.ย Youโ€™llย collaborate closely with stakeholders to understand their data needs, design efficient and reliable data pipelines, and deliver dashboards and insights that power smarter decisions. This is not your typical reporting role โ€”ย youโ€™llย be helping shape how Propelย leveragesย modern data stack tools likeย Snowflake,ย dbtย Cloud,ย Glean,ย andย Domoย to build scalable, intelligent solutions including next-generationย Snowflake AI-driven analytics.ย 

Responsibilities

  • Design, build, andย maintainย scalable analytics data models and transformations inย dbtย Cloud and Snowflake.ย 
  • Develop reliable, reusable datasets and business-ready data products that support reporting, analysis, experimentation, and operational decision-making.ย 
  • Improve the structure, quality, and maintainability ofย Propelโ€™sย analytics engineering ecosystem, with a focus on consistency, performance, and trust.ย 
  • Help define and evolveย Propelโ€™sย semantic layer, core metrics, and businessย logicย so teams are aligned on how performance is measured.ย 
  • Lead efforts to document, standardize, and centralize key business definitions within a governed data dictionary.ย 
  • Partner with cross-functional stakeholders (Product,ย Operations, Marketing, Finance, Risk, Compliance) to understand businessย objectivesย and translate them into scalable data solutions.ย 
  • Build andย maintainย dashboards and reportsย that clearly answer key business questions and drive decision-making.ย 
  • Identifyย trends, patterns, and opportunities through creative analysis and critical thinking.ย 
  • Troubleshoot andย optimizeย SQL queries and pipelines for efficiency and reliability.ย 
  • Contribute to the development of AI-powered analytics and data enrichment initiatives within Snowflake.ย 

ย 

Requirements

  • Bachelorโ€™s degree in Computer Science, Finance, Economics, Analytics, Business, Math, Statistics, orย a related field.
  • 5+ years of hands-on analytical experience in a professional or business setting, ideally within fintech or a fast-paced data-driven organization.
  • Advanced SQL skills with proven experience querying and transforming large datasets inย Snowflakeor similar data warehouses.ย 
  • Strong data visualization and storytelling skills using tools likeย Domo,ย Tableau, orย Power BI.
  • Experience with data transformation and modeling (e.g.,ย dbt).
  • Excellent problem-solving and critical-thinking skills โ€” youย donโ€™tย just answerย questions,ย you help people ask better ones.
  • Strong communicationย skills โ€” able to collaborate effectively with technical and non-technical stakeholders.
  • Proven ability to manage multiple priorities and deliver high-quality work under tight timelines.
  • Experience using generative AI tools (e.g., ChatGPT, Claude, Copilot) is an asset
  • Ability to integrate or adopt AI tools in day-to-day tasks

Benefits to Joining Propel

  • Growth and opportunity โ€“ we pride ourselves on promoting from within
  • Incredible company culture
  • Competitive salary and health benefits
  • Comprehensive vacation package
  • Group health and dental benefits
  • Group RRSP program
  • Support for new parents
  • Diverse and inclusive workplace

ย 

Salary Range

$65,000 โ€“ $85,000

Final compensation is determined by market conditions, location, and the candidateโ€™s experience, skills, and education. This role may also be eligible for performance-based incentive programs and total compensation may include variable incentives, such as bonuses and commissions.

ย 

This posting is for an existing vacancy within our organization.

ย 

Our Culture

Propel brings together the brightest talent to build opportunities. We are entrepreneurs who measure success through results and growth from within; talent and hard work never go unnoticed. Our team fosters curiosity and growth, making Propel one of North Americaโ€™s fastest-growing companies and a Best Place to Work.

ย 

Commitment to Diversity & Inclusion

Propel welcomes and encourages applications from all groups, including Indigenous peoples, women, visible minorities, persons with disabilities, people from gender and sexually diverse communities, and those with intersectional identities. Should you require accommodation throughout any stage of the recruitment and selection process, please specify your requirements when submitting your application and we will work with you to meet your needs.

AI Disclosure

We use AI to assist in reviewing applications and assessing candidates. These tools support our recruitment team, however, all hiring decisions are made by ourย trained hiring managers and recruitment professionals, not AI.