1

Quant Engineer Jobs in Toronto, ON (NOW HIRING)

Advanced academic background in a quantitative discipline such as Computer Science, Engineering, Mathematics, or a related field. * Excellent communication skills, a coaching mindset, and the ability ...

BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred. * Experience building Conversational and Agentic AI solutions.

BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred. * Experience building Conversational and Agentic AI solutions.

Qualitative and Quantitative Assessment; Presentation; Analytical. PHYSICAL WORK ENVIRONMENT The physical demands described here are representative of those that must be met by an employee to ...

Principal Software Engineer The global capital markets are among the largest markets in the world ... and quantitative and qualitative attributes within. This fundamental need plus a booming market ...

The Opportunity This Senior Developer/Business Analyst role within Quantitative and Technology Services (QTS), consists of developing, improving and supporting strategic applications within the RAMPP ...

Qualifications Bachelor's or Graduate degree in Engineering, Computer Science, Mathematics, Physics, or related quantitative discipline. Strong programming skills in Python, Scala, or Java, with a ...

Staff Machine Learning Engineer

Toronto, ON ยท Remote

$212K - $301K/yr

Join EvenUp as a Staff Machine Learning Engineer and help set the technical direction for how ... PhD in Machine Learning, Computer Science, or a related quantitative field. * Experience with ...

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 ...

Staff Software Engineer The global capital markets are among the largest markets in the world ... and quantitative and qualitative attributes within. This fundamental need plus a booming market ...

Mechanical Design Engineer II

Brampton, ON ยท On-site

CA$80K - CA$90K/yr

Mechanical Design Engineer II The Mechanical Design Engineer II within our Production Engineering ... Has strong analytical design and quantitative problem-solving skills Preferably a candidate will ...

Master's (MASc/MSc) or PhD in Engineering, Applied Science, Physics, or a highly quantitative, related field. * Core Specializations of Interest: Electrical/Electronics Engineering, Aerospace ...

Senior Platform Engineer

Toronto, ON ยท Hybrid

CA$75K - CA$141K/yr

Bachelor's or Graduate degree in Engineering, Computer Science, Mathematics, or related quantitative discipline. * 7+ years of experience supporting Data Management platforms, including Data Catalog ...

We are seeking a UI React Developer with strong Redux experience to join the Quantitative and Technology Services (QTS) team, developing, improving, and supporting strategic applications within the ...

Showing results 41-60

Quant Engineer information

What is the salary of a quant engineer?

The salary of a quant engineer typically ranges from $100,000 to $200,000 annually, with higher compensation for those with advanced degrees, extensive experience, or specialized skills in programming languages like Python or C++. In addition to base salary, many quant engineers receive bonuses and performance incentives, especially in financial firms or hedge funds.

What are the key skills and qualifications needed to thrive as a quant engineer, and why are they important?

To thrive as a Quant Engineer, you need strong quantitative and programming skills, typically supported by a degree in mathematics, physics, computer science, or a related field. Proficiency in programming languages such as Python, C++, or Java, as well as familiarity with statistical analysis tools and financial modeling systems, is essential. Analytical thinking, problem-solving abilities, and effective communication distinguish top performers in this role. These skills enable Quant Engineers to develop robust models and algorithms that drive accurate trading strategies and risk management in fast-paced financial environments.

What is a quant engineer?

Quant Engineers, or quantitative engineers, are professionals who apply mathematical models, statistical techniques, and computer programming to solve complex problems in finance and related industries. They often work on designing trading algorithms, risk management tools, and pricing models for financial instruments. Quant Engineers typically have strong backgrounds in mathematics, computer science, and finance, and are skilled in programming languages such as Python, C++, or R. Their work helps financial firms make data-driven decisions and optimize strategies in highly competitive markets.

What is the difference between Quant Engineer vs Quant Analyst?

AspectQuant EngineerQuant Analyst
Required CredentialsDegree in Math, Finance, or Computer Science; often requires programming skillsDegree in Finance, Economics, or Math; less emphasis on programming
Work EnvironmentDevelops models, algorithms, and software tools for trading and risk managementAnalyzes data, interprets models, and provides insights for trading strategies
Employer & Industry UsageFinancial firms, hedge funds, investment banksFinancial firms, asset management, hedge funds

While both roles involve quantitative analysis, Quant Engineers focus on building and implementing models and software, whereas Quant Analysts primarily analyze data and interpret models to inform trading decisions. The roles often overlap but differ in technical depth and responsibilities.

How do quant engineers typically collaborate with traders and other team members to develop and implement trading strategies?

Quant Engineers work closely with traders, researchers, and software developers to design, test, and refine quantitative trading models. They often translate mathematical models into efficient code, analyze large datasets, and ensure strategies are both robust and scalable for real-time trading environments. Frequent communication is key, as Quant Engineers must gather requirements from traders, iteratively backtest ideas, and adapt models based on feedback and market changes. This collaborative process helps ensure strategies are both scientifically sound and practically viable for deployment.
Infographic showing various Quant Engineer job openings in Toronto, ON as of August 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Hybrid job distribution.

Principal Data Engineer

Xplore Inc.

Markham, ON โ€ข On-site

Other

Posted 9 days ago


Job description

Xplore Inc. is Canadaโ€™s fibre, 5G and satellite broadband company for rural living. Xplore is committed to the relentless pursuit of an improved broadband experience for all Canadians. Xplore is building a world-class fibre optic and 5G wireless network to enable innovative broadband services for better every day rural living, for today and future generations.

This role is for an experienced technical leader to lead the technical roadmap and upskill the Xplore data engineering team. You will define the end-to-end data platform (ingestion, storage, modeling, governance, quality, observability), unify data currently siloed across on-prem network/OSS/BSS systems, Salesforce CRM, and other business sources, and embed compliance, lineage, and cataloging by design.

Key responsibilities include:
  • Own the architecture and delivery of a scalable enterprise lakehouse platform following the medallion pattern (bronze/silver/gold layers) to support BI, data science, and AI use cases.
  • Stand up robust ingestion pipelines from on-prem and cloud systems (e.g., SQL Server/Oracle, network telemetry/OSS, Salesforce via APIs/CDC), enabling both batch and streaming workloads.
  • Implement governance, security, and compliance controls end-to-end: role-based and attribute-based access control, row/column-level security, secrets and key management, data retention, and privacy-by-design aligned to Canadian regulations (e.g., PIPEDA/CPPA, Quebec Law 25) and other relevant standards.
  • Establish enterprise data lineage and cataloging using modern metadata management and data discovery tools; curate business glossaries and data contracts with domain owners.
  • Define data quality SLAs/SLOs and automated validation at ingestion and transformation stages; implement observability and alerting for freshness, volume, and schema drift.
  • Partner with analytics, data science, and AI/ML teams to provision clean, well-documented datasets and features, and enable MLOps-friendly patterns.
  • Lead engineering best practices: CI/CD, infrastructure as code, cost governance, performance tuning, and FinOps reporting (tracking and optimizing cloud/data platform spend).
  • Create reference architectures, standards, and reusable frameworks; mentor data engineers and champion engineering excellence and security-first development.
  • Collaborate across information security, privacy, legal, and compliance domains to translate policies into technical controls, and to support audits and evidence collection.
  • Engage with business stakeholders to prioritize the roadmap, translate use cases into data products, and measure value delivered.
  • Build, mentor, and inspire a high-performing data engineering team; establish best practices for reproducibility, testing, and documentation
The ideal candidate will possess:
  • 10+ years of data engineering experience, including 4+ years leading platform or team-level initiatives.
  • Expert hands-on skills with modern data lakehouse and distributed compute platforms (e.g., Spark-based ecosystems, cloud-native storage, streaming frameworks).
  • Strong experience with enterprise data cataloging, lineage, and governance at scale.
  • Proficiency in Python and/or Scala, advanced SQL, and performance tuning for large-scale ELT.
  • Practical knowledge of ingestion from Salesforce, on-prem RDBMS, files/telemetry, and APIs; experience bridging on-prem systems with cloud platforms.
  • Solid grasp of security and privacy controls (RBAC, encryption, tokenization/masking), and familiarity with Canadian privacy regimes (PIPEDA/CPPA, Law 25) and other relevant standards.
  • Experience with CI/CD, infrastructure as code, automated testing frameworks, and data observability solutions.
  • Comfort collaborating across domains (Network, Care, Marketing, Finance, Sales) and translating business needs into scalable data products.
  • Advanced academic background in a quantitative discipline such as Computer Science, Engineering, Mathematics, or a related field.
  • Excellent communication skills, a coaching mindset, and the ability to set platform vision and deliver iteratively.


Condition of Employment:

As a condition of employment and in order to comply with industry related data security standards, this position is subject to the successful completion of a Criminal Background Check. Details will be supplied to applicants as they move through the selection process.

Xplore is committed to creating an accessible environment and will accommodate disabilities during the selection process. Please let your recruiter know during the selection process of any accommodation needs.