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Financial Engineering Jobs in Toronto, ON (NOW HIRING)

Alquemy

Senior .NET Developer

Toronto, ON

You will operate at the intersection of sophisticated financial engineering and high-performance computing, building the backbone for complex derivative valuation and risk management This is a role ...

Synechron

Quantitative Developer with MatLab

Toronto, ON · Hybrid

CA$130K - CA$140K/yr

Bachelor's degree in Computer Science, Engineering, Quantitative Finance, or a related discipline. * MATLAB:Expert proficiency in developing, validating, and deploying complex mathematical models and ...

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All JobsFinancial Engineering JobsFinancial Engineering Jobs in Toronto, ON

Financial Engineering information

See Toronto, ON salary details

$28.2K

$101.8K

$185.6K

How much do financial engineering jobs pay per year?

As of Aug 7, 2026, the average yearly pay for financial engineering in Toronto, ON is $101,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,600.00 and $143,628.00 per year, depending on experience, location, and employer.

What is the difference between Financial Engineering vs Quantitative Analyst?

AspectFinancial EngineeringQuantitative Analyst
Required CredentialsDegree in Financial Engineering, Mathematics, or related fields; often certifications like CQFDegree in Finance, Mathematics, or Statistics; certifications like CFA or CQF are common
Work EnvironmentFinancial institutions, hedge funds, investment banks; focus on product development and risk managementTrading desks, asset management firms; focus on data analysis and model development
Employer & Industry UsageUsed in risk management, derivatives pricing, and structured productsUsed in trading strategies, portfolio management, and risk assessment

Financial Engineering and Quantitative Analysts often share similar educational backgrounds and work in related financial sectors. While Financial Engineers focus on creating financial products and managing risks through complex models, Quantitative Analysts primarily analyze data to inform trading and investment decisions. Both roles require strong quantitative skills and often overlap in financial institutions.

What is financial engineering?

Financial engineering is the application of mathematical techniques, computer science, and statistical methods to solve problems and create innovative solutions in finance. Professionals in this field develop new financial products, manage risk, and optimize investment strategies using quantitative models. Financial engineers often work in banks, investment firms, hedge funds, or financial technology companies, helping organizations manage complex financial systems and products. The discipline combines finance, mathematics, statistics, and programming to address challenges in areas like derivatives pricing, risk management, and portfolio optimization.

What jobs do financial engineers get?

Financial engineers typically work as quantitative analysts, risk managers, derivatives traders, or financial modelers in banks, investment firms, hedge funds, and financial technology companies. They use skills in mathematics, programming, and financial theory to develop models for pricing, trading, and risk assessment. Certifications like CFA or FRM can enhance job prospects in this field.

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

To thrive as a Financial Engineer, you need a strong background in quantitative analysis, mathematics, programming, and finance, typically supported by a relevant degree such as financial engineering, mathematics, or computer science. Expertise in programming languages like Python, R, or C++, as well as familiarity with financial modeling software and risk management systems, is essential. Strong problem-solving, analytical thinking, and communication skills set top performers apart in this role. These skills are crucial for designing innovative financial products, managing complex risks, and translating quantitative insights into actionable business strategies.

What are some common challenges faced by financial engineers when implementing quantitative models in real-world financial institutions?

Financial engineers often encounter challenges such as aligning complex quantitative models with existing IT infrastructure and ensuring the models comply with regulatory requirements. Additionally, translating theoretical models into practical, scalable solutions that can handle large volumes of real-time data requires close collaboration with software developers and risk managers. Effective communication with non-technical stakeholders is also crucial, as financial engineers must explain model assumptions and results to decision-makers from diverse backgrounds.
What are the most commonly searched types of Financial Engineering jobs in Toronto, ON? The most popular types of Financial Engineering jobs in Toronto, ON are:
What job categories do people searching Financial Engineering jobs in Toronto, ON look for? The top searched job categories for Financial Engineering jobs in Toronto, ON are:
Financial Engineering jobs near you
Infographic showing various Financial Engineering job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $101,771 per year, or $48.9 per hour.

Software Engineer - Financial Engineering

Spotify

Toronto, ON

Full-time

Medical, Dental, Retirement, PTO

Posted 28 days ago

Job description

The Platform team creates the technology that enables Spotify to learn quickly and scale easily, enabling rapid growth in our users and our business around the globe. Spanning many disciplines, we work to make the business work; creating the infrastructure, tooling, frameworks, and capabilities needed to welcome a billion customers.

Spotify's Financial Engineering (FinE) organization ensures that as Spotify grows, our financial systems grow with it. We build the infrastructure and tooling that finance teams across the company depend on to track revenue accurately, report reliably, and reconcile at scale.

The Oracles team sits at the heart of Spotify's financial infrastructure, building the data pipelines and backend services that power our subledger and accounting lifecycle. As part of a broader Financial Engineering initiative, we're standardizing and scaling how accounting data flows across Spotify. You'll partner with engineers, finance teams, and product managers to build reliable, scalable systems that simplify complex financial processes.

We're looking for a Software Engineer who enjoys building reliable, data-intensive systems. You'll help shape the future of Spotify's financial data platform by designing robust data models, developing scalable backend services, and building high-volume data pipelines that power critical financial workflows.

What You'll Do
  • Build, operate, and evolve scalable Scio data pipelines on Google Cloud Platform that process high-volume financial data with accuracy and reliability.
  • Develop and enhance Java backend services that power integrations across Spotify's financial ecosystem.
  • Design and evolve data models and datasets that support accounting, reconciliation, financial reporting, and operational insights.
  • Build and improve integrations with external financial systems to bring critical financial data into Spotify's financial ecosystem.
  • Partner closely with Finance, Product, and Engineering teams to translate accounting requirements into reliable, scalable technical solutions.
  • Improve the scalability, observability, and resilience of financial data pipelines and backend services.
  • Contribute to engineering best practices through continuous delivery, automated testing, monitoring, and thoughtful code reviews.
  • Help drive technical decisions that improve the long-term maintainability of Spotify's financial engineering platform.
Who You Are
  • You have 3+ years of professional experience building backend systems and data-intensive applications.
  • You are experienced with Scala or Java and at least one distributed data processing framework such as Scio, Apache Beam, Spark, or Flink.
  • You know how to design and build reliable backend services and scalable data pipelines that support business-critical workflows.
  • You have experience designing data models that enable accurate, high-volume financial processes.
  • You have worked with workflow orchestration platforms such as Flyte, Airflow, or similar technologies.
  • You care deeply about engineering fundamentals, including continuous delivery, automated testing, monitoring, and writing production-quality code.
  • You enjoy collaborating with cross-functional partners and translating complex business requirements into elegant technical solutions.
  • Experience working within financial, accounting, or other regulated data domains is a plus.
  • A Bachelor's degree or higher in Computer Science or a related field is a plus.
Where You'll Be
  • This role is based in Toronto.
  • We offer you the flexibility to work where you work best! There will be some in-person meetings, while still allowing flexibility to work from home.
The Canada base range for this position is CAD 103,321.00-147,602.00, plus equity. Benefits available for this position include extended health and dental coverage, retirement savings plans, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, and other benefits in accordance with Canadian employment standards. These ranges and benefits may be modified in the future.

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It's in our differences that we will find the power to keep revolutionizing the way the world listens.
 
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we're here to support you in any way we can.
 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice
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