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Analytics Engineer Jobs in Ontario (NOW HIRING)

Partner with Professional Services to extract, transform, and analyze client data to optimize ... Collaborate with Product, Engineering, and Customer Success to deliver high-quality, actionable ...

... practices for analytics engineering, data quality, and AI-ready data design across the team. What do you need to succeed? Must have : * 10+ years of progressive experience as a data analyst ...

Experience with data modeling, ETL architecture, and designing schemas that serve diverse analytical and ML use cases * Strong programming experience across at least two of Java, Go, Python, and SQL

Primary Responsibilities The primary duty of the CFD Engineer / Analyst is to aid in modelling efforts using computational fluid dynamics (CFD) software that will optimize building designs, deliver ...

New

Manager, Risk Data Analytics

Toronto, ON · On-site

CA$82K - CA$154K/yr

Data Analytics & Reporting The Manager, Data Analytics is responsible for leading the development ... Programming (e.g., Python, SQL) * SAS only nice to have for legacy purposes not mandatory * Data ...

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep ... We are seeking an experienced Data Engineer to join our team, specifically focused on building ...

Showing results 21-40

Analytics Engineer information

See Ontario salary details

$62.5K

$109.1K

$178K

How much do analytics engineer jobs pay per year?

As of Aug 7, 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 do analytics engineers do?

Analytics engineers design, build, and maintain data pipelines and infrastructure to enable data analysis and reporting. They work with tools like SQL, Python, and data warehouses to ensure data is accurate, accessible, and well-structured for analysts and data scientists. Their role often involves collaborating with teams to optimize data workflows and ensure data quality.

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:
Infographic showing various Analytics Engineer job openings in Ontario as of August 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 88% In-person, and 12% Remote job distribution, with an average salary of $109,135 per year, or $52.5 per hour.

CA$130K - CA$160K/yr

Full-time

Re-posted 17 days ago


Job description

Our Story

About You:You are a high achiever looking to thrive in a fast-paced environment. You take pride in your own work but are comfortable collaborating with a team of highly motivated individuals. You can communicate clearly and concisely with teammates and clients, and you enjoy strong company culture and camaraderie. You can navigate multiple corporate functions, including global lines of service and corporate centers of excellence. You possess strong interpersonal skills and are willing to take on diverse tasks to achieve the team's common goal. You value personal and professional growth and are ready to take the next step in advancing your career.If this sounds like you, well, then you will love the culture at Avison Young!About Us:Avison Young is a global commercial real estate brokerage and advisory firm, offering transaction, management, financial and consulting services. We've designed our corporate structure to best serve our clients by enhancing collaboration across our organization.Real estate can have an enormous positive impact on people's lives - and we're in the business of making spaces and places work better for people. Our purpose is to create real economic, social and environmental value as a global real estate advisor, powered by people.We care about each other and we have each other's backs. This makes Avison Young a great place to be a client, and a great place to work. We support the whole person and their complete wellness - economic, mental and physical - because what's best for our business comes from our people bringing their whole selves to work.

Of course we love it here, but outsiders think we're pretty great too! Avison Young has been recognized as one of Canada's Best Managed Companies for the 13th year in a row, with a Platinum Club designation! 

Overview

As Lead, Analytics Engineering at Avison Young Technologies, you will lead the strategy and execution of our proprietary data products and models that empower commercial real estate decision makers across investor, occupier, and public sector client segments. You will partner with our clients, advisory team, and leadership to design solutions that support complex use cases across portfolio analysis, site and market search, and highest and best use.

The ideal candidate combines deep familiarity with commercial real estate strategy and data with strong product management expertise to translate complex needs into scalable, insight-driven solutions.  They excel at partnering with stakeholders to shape strategy and test value and with engineering teams to deliver usable products.

The base salary is aligned with market data and is estimated to be between $130,000 to $160,000 with the ability to achieve additional compensation through a bonus. This salary range reflects base compensation for the position across all Canadian locations. Within this range, individual pay is determined by work location and other factors, including relevant education/training, experience, and internal equity. This posting is for an existing vacancy withing our organization.

Responsibilities
  • Lead the full lifecycle - from discovery and concept development, to test, scale, launch, and iteration - for data products and data science models.
  • Develop mathematical and algorithmic approaches to address complex commercial real estate decisions overseeing the work of the data science and data engineering teams.
  • Participate in the daily development processes with the engineering, data science, and product teams to deliver usable data products, directly contributing to the business and technical requirements and testing and validation of the data products.
  • Manage data and technology vendor relationships through renewals, delivery timeliness, and data evaluation.
  • Ensure compliance and responsible data usage and governance practices across all data products and workflows.
  • Collaborate with clients, advisory team, and leadership to assess client needs, test value, and guide direction of data products.
  • Support go-to-market teams with positioning and product market fit of new and upcoming products.
  • Communicate strategy, roadmap and release plans to internal stakeholders and to clients.
  • Define and track success metrics on delivered data products.
  • And other duties as assigned.
Qualifications
  • Minimum of 10 years of experience in commercial real estate strategy, with at least 5 years working directly with technology, data, and analytics.
  • Bachelor's degree in data analytics, data engineering, business, real estate, or a related field.
  • Strong understanding of SQL, data architecture, data pipelines, and geospatial datasets.
  • Strong understanding of commercial real estate strategy.
  • Excellent verbal, written, and presentation skills.
  • A self-starter with a proactive and entrepreneurial mindset. Proven ability to influence without authority and build strong, collaborative relationships across teams.
Workplace TypeOn-SiteOur Equal Opportunity Commitment

Avison Young practices as an equal opportunity employer in all services locations around the world.  We are committed to building and maintaining a workforce diverse in experience, skills and knowledge with uniformity in service excellence, commitment and integrity. 

The firm maintains a strict policy to ensure employment opportunities are equal and do not discriminate based on race, color, religion, creed, age, sex, gender, gender identity or expression, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, protected veteran or military service status, or any other elements protected by law.

Avison Young welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates during the recruitment process. For those requiring assistance, information relating to the need for accommodation and accommodation measures will be addressed confidentially. 

Avison Young is committed to employing the best talent with the most fair and equitable recruitment practices. Apply with us TODAY! 

Employment Type: FULL_TIME