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Quantitative Data Engineer Jobs in Toronto, ON (NOW HIRING)

Nasdaq

Director,Quantitative Data Products

Toronto, ON · Hybrid

CA$121K - CA$170K/yr

Director, Quantitative Data Products Nasdaq's Alternative Data group specializes in creating unique ... Partner with cross-functional teams including data science, data engineering, partnerships, client ...

Klick Health

Data Engineer

Toronto, ON · Hybrid

D.) in Computer Science, Data Engineering, Data Science, or a related quantitative field * Knowledge of database design and data modeling principles within modern analytics platforms * Experience ...

Ci

Data Engineer

Toronto, ON · On-site

CA$69K - CA$119K/yr

We are currently seeking a Data Engineer to join the Data and Analytics team in the Wealth ... Post-secondary degree in a quantitative discipline. Knowledge, Skills, and Abilities * Solid ...

Synechron

Quantitative Developer with MatLab

Toronto, ON · Hybrid

CA$130K - CA$140K/yr

... , Data, and Software Engineering, servicing an array of noteworthy financial services and ... Our challenge We are seeking a highly skilled and motivated Quantitative Developer to join our ...

Royal Bank of Canada

Lead Data Engineer

Toronto, ON · Hybrid

Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or related quantitative discipline * 3+ years of experience as a Data Engineer or similar role * Advanced proficiency in ...

Manulife

Lead Data Engineer (Director Level)

Toronto, ON · Hybrid

Bachelor's degree (or higher) in computer science or quantitative field (e.g., Mathematics, Physics, Engineering). * Advanced experience with databases, data architecture, and modern data engineering ...

New

Ci

Senior Data Engineer

Toronto, ON

CA$69K - CA$119K/yr

We are currently seeking for a Senior Data Engineer to join the Data and Analytics team in the ... Post-secondary degree in a quantitative discipline. Knowledge, Skills, and Abilities

Cmcmarkets

Quantitative Trader

Toronto, ON

Apply a data-driven approach to all strategy decisions using Python and other analytical tools to ... Mathematics, Engineering, Physics, Computer Science). * Internship or early-career experience in ...

Jay Analytix

Quantative Developer

Toronto, ON · On-site

Quantitative Developer Location: Toronto, Ontario, Canada Hybrid Employment Type: Contract About ... Strong experience with data analysis and numerical computing. * Familiarity with SQL and data ...

Jay Analytix

Quantative Developer

Toronto, ON · Hybrid

Quantitative Developer Location: Toronto, Ontario, Canada - Hybrid Employment Type: Contract About ... Strong experience with data analysis and numerical computing. * Familiarity with SQL and data ...

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All JobsQuantitative Data Engineer JobsQuantitative Data Engineer Jobs in Toronto, ON

Quantitative Data Engineer information

What are the key skills and qualifications needed to thrive as a Quantitative Data Engineer, and why are they important?

To excel as a Quantitative Data Engineer, you need strong proficiency in programming (such as Python, R, or C++), advanced mathematical and statistical knowledge, and a relevant degree in computer science, mathematics, or a related field. Experience with big data tools (like Spark, Hadoop), cloud platforms, and data pipeline systems, as well as familiarity with financial data sets, is typically required. Analytical thinking, detail orientation, and effective problem-solving skills distinguish top performers in this role. These competencies are critical for efficiently transforming complex data into actionable insights and supporting robust quantitative models in data-driven environments.

What is a Quantitative Data Engineer?

A Quantitative Data Engineer is a professional who designs, builds, and maintains data infrastructure that supports quantitative analysis, typically in finance or technology sectors. They work closely with quantitative analysts and data scientists to ensure efficient data pipelines, data quality, and high-performance systems for processing large datasets. Their responsibilities include developing ETL processes, optimizing databases, and implementing data models to support research and trading strategies. Strong programming skills, expertise in big data technologies, and knowledge of quantitative methods are essential for this role.

What is the difference between Quantitative Data Engineer vs Data Scientist?

AspectQuantitative Data EngineerData Scientist
Primary FocusBuilding data pipelines, data infrastructure, and ensuring data qualityAnalyzing data, creating models, and deriving insights
Skills & ToolsSQL, Python, Spark, ETL processes, data architectureStatistics, machine learning, Python/R, data visualization
CredentialsComputer science, engineering, or related degrees; certifications in data engineeringStatistics, data science, or related degrees; certifications in data analysis or machine learning
Work EnvironmentData engineering teams, data infrastructure projectsData analysis teams, research, and modeling projects

While both roles work closely with data, Quantitative Data Engineers focus on building and maintaining data systems, whereas Data Scientists analyze data to generate insights and models. They often collaborate but have distinct skill sets and responsibilities within data-driven organizations.

How does a Quantitative Data Engineer typically collaborate with data scientists and quantitative analysts on projects?

Quantitative Data Engineers work closely with data scientists and quantitative analysts to design, build, and optimize data pipelines that support complex modeling and analytics. They are often responsible for ensuring data quality, scalability, and efficient data processing, enabling analysts to focus on developing models and extracting insights. Regular collaboration includes translating analytical requirements into technical solutions, troubleshooting data issues, and iterating on data infrastructure to support evolving project needs. This teamwork fosters an environment where technical and analytical expertise complement each other, leading to more robust and actionable results.
What are popular job titles related to Quantitative Data Engineer jobs in Toronto, ON? For Quantitative Data Engineer jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Quantitative Data Engineer jobs in Toronto, ON look for? The top searched job categories for Quantitative Data Engineer jobs in Toronto, ON are:
Quantitative Data Engineer jobs near you
Infographic showing various Quantitative Data Engineer job openings in Toronto, ON as of June 2026, with employment types broken down into 2% As Needed, 91% Full Time, 5% Part Time, and 2% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

Director,Quantitative Data Products

Nasdaq

Toronto, ON • Hybrid

CA$121K - CA$170K/yr

Full-time

Re-posted yesterday

Job description

Director, Quantitative Data Products
Nasdaq's Alternative Data group specializes in creating unique and insightful data products from non-traditional data sources. Well-known examples of Alternative Data include sentiment measures, real-time tracking of vehicles via GPS transponders, satellite monitoring of industrial facilities, and consumer insights gleaned from anonymized credit card transactions. Our data products empower some of the world's most sophisticated investment funds to outperform.
As Director of Quantitative Data Products, you'll play a critical role in defining strategy and driving execution of a portfolio of innovative Alternative Data products. You'll thrive in this position if you're entrepreneurial, data-driven, and strategic, with a deep understanding of investments and a passion for creating products that generate real business impact in a fast-paced, high-growth environment. The ideal candidate has trade floor and/or investments experience, with a strong understanding of buy-side and sell-side trading workflows.
Key Responsibilities
  • Conduct market research and engage directly with clients to identify new product opportunities and validate concepts.
  • Own the full product lifecycle from ideation and validation through launch, scale, and ongoing optimization.
  • Develop and prioritize product roadmaps that align with business objectives and drive measurable revenue growth.
  • Partner with cross-functional teams including data science, data engineering, partnerships, client success, sales, and marketing to design and deliver innovative data products.
  • Drive go-to-market strategy, including pricing, positioning, and sales enablement to maximize product adoption and success.
Required Qualifications
  • 10+ years of experience in product management, product development, and/or data analysis within the investment industry.
  • Deep understanding of capital markets, data product fundamentals, and data feeds/products.
  • Proven ability to conceptualize and drive new initiatives from 0-to-1 in a fast-paced and entrepreneurial environment.
  • Excellent communicator with strong stakeholder management skills and a revenue-focused, owner mindset.
  • Bachelor's degree in finance, economics, computer science, engineering, or related discipline.
Preferred Qualifications
  • Strong understanding of the alternative data landscape, including key companies and products/services, as well as their competitive positioning.
  • Experienced in evaluating and applying alternative data to the investment lifecycle (i.e., programming, statistics, backtesting, etc).
  • 0-to-1 startup or venture-building experience.
This position will be located in Toronto and offers the opportunity for a hybrid work environment at least 3 days a week in-office, subject to change, providing flexibility and accessibility for qualified candidates.

Come as You Are

Nasdaq is an equal opportunity employer. We welcome applications from candidates of all backgrounds and identities.

We are committed to fostering an inclusive workplace where diverse perspectives, experiences, and identities are valued and celebrated.

We ensure that individuals with disabilities are provided with reasonable accommodation throughout the hiring process.

What We Offer

We're proud to offer a competitive rewards package that is meaningful, recognizes the unique needs of our employees and their families and incentivizes employees for their contribution to Nasdaq's overall success.

The base pay range for this role is $121,000 - $170,000. In addition to base salary, Nasdaq provides a generous annual bonus/commission (short-term incentive), and equity (long-term incentive), comprehensive benefits, and opportunity for growth. Exact compensation may vary based on several job-related factors that are unique to each candidate, including but not limited to: skill set, experience, education/training, business needs and market demands.

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