Quantitative Data Engineer (CFA or Phd) - Toronto, ON / Montreal, QC / Boston, MA (hybrid)
Quick Overview
Job Description
Quantitative Data Engineer
CFA Level I passed or enrolled OR PhD / Master's in a quantitative field
Hiring Company: Epik Solutions
| Location | Toronto, ON / Montreal, QC / Boston, MA (hybrid) |
| Role type | Full-time Fast-track development role |
| Experience | 1+ years (or exceptional new-grad) |
| Team | Global Wealth & Asset Management (GWAM) Data Office |
The Opportunity
We are building an elite, domain-deep data engineering team for a leading global asset & wealth management client.. This is a launchpad role for outstanding early-career engineers who want to sit at the intersection of data engineering and investment management. You'll be developed into a rare hybrid: an engineer who speaks the language of both data platforms and capital markets.
What You'll Do
- Build and maintain Azure/Databricks data pipelines for investment and risk data under senior mentorship.
- Support curation, transformation and DAL layers; write validation and QA automation.
- Learn asset-management workflows (AUM, portfolio risk, performance) hands-on.
Must-Have Qualifications
- 1+ years' experience (or exceptional new-grad) with Python, SQL, and a cloud data stack; strong CS/engineering/quant fundamentals.
- Evidence of outstanding quality - top academics, competitions, publications, or high-impact projects.
- Either CFA Level I passed or enrolled OR PhD / Master's in a quantitative field (see qualifying disciplines below).
- Genuine interest in asset management and financial markets.
Advanced Quantitative Education - What Qualifies
A PhD or Master's degree in a quantitative field is a strong asset. Qualifying disciplines include:
| Field cluster | Example degrees | Why it matters |
| Financial Engineering / Quant Finance | MFE, MSc Financial Engineering, PhD Mathematical Finance | Fluency in portfolio theory, risk, derivatives, performance |
| Applied Mathematics & Statistics | MSc/PhD Statistics, Applied Math, Actuarial Science | Risk modelling, factor analysis, time-series methods |
| Computer Science / Data Science / ML | MSc/PhD CS, Machine Learning, Data Science | Core to data engineering and agentic AI |
| Econometrics / Quant Economics | MSc/PhD Econometrics, Quantitative Economics | Market data, forecasting, analytics |
| Physics / Engineering (quant-heavy) | PhD Physics, Computational Eng., Operations Research | Advanced modelling, optimization, numerical methods |
Who You Are
An ambitious, high-caliber early-career professional who wants to grow fast in a collaborative team and become a CFA-credentialed data engineer.
Skills
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