Quantitative Data Engineer (CFA/PhD) – Toronto/Montreal/Boston
Overview
This role owns the data infrastructure for a global wealth management client, supporting 1+ years of experience or exceptional new grads. You will join the Global Wealth & Asset Management (GWAM) data office, a fast-track development team building domain-deep data solutions. The role distinguishes itself by requiring CFA Level I or a PhD or Master's in a quantitative field, offering a unique blend of finance and data engineering. You will work hybrid in Toronto, Montreal, or Boston, directly impacting investment decisions with Python, SQL, and AWS.
What You'll Do7
- 1Build ETL pipelines with Python and SQL to process financial data for GWAM clients.
- 2Design data models for portfolio analytics, using AWS services like S3, Glue, and Redshift.
- 3Collaborate with quantitative analysts to implement risk and performance metrics in Spark.
- 4Automate data quality checks and monitoring with Airflow.
- 5Ship production-ready data feeds for downstream consumption by investment teams.
- 6Debug and optimize data transformations to meet SLAs for daily reporting.
- 7Document data lineage and maintain data dictionaries for regulatory compliance.
Requirements6
- 1CFA Level I passed or enrolled, OR PhD or Master's in a quantitative field (e.g., Mathematics, Physics, Finance).
- 21+ years building data pipelines with Python and SQL (or exceptional new-grad with strong coursework).
- 3Experience with cloud data platforms, preferably AWS.
- 4Familiarity with Spark or Airflow for large-scale data processing.
- 5Strong problem-solving skills in a fast-paced environment (remove generic? but source implies).
- 6Excellent communication for cross-functional collaboration.
Salary Insight
$60k per year
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