ETF Systems Engineer

Job Title: ETF Systems Engineer

Location: Toronto, ON (Hybrid model • up to four days in office, subject to space availability)

Duration: 12 months

Contract Type: T4 only

Pay Rate: $55.17 • $60.69/Hour

Role Mandate:

These specialist roles will be part of the analytics and business intelligence team, supporting the development and build-out of ETF analytics systems at Global Asset Management team.
The candidates will advance the platform development across different asset classes.
The role blends expertise in financial markets and quantitative investing with strong technology and data skills.
The successful candidate will contribute to the development of the bank's quantitative investment platform, automate portfolio management workflows, and deliver analytics support to business users.
Collaboration is key—this role involves working closely with data engineers and front-office investment professionals.

Role Responsibilities:

Collaborate with portfolio managers to improve the technology platform supporting daily investment workflows.
Partner with Data Engineers and Business Analysts to build data pipelines and automate routine tasks.
Support re-design of legacy proprietary investment analytics frameworks, facilitating their transformation and migration to cutting edge infrastructure.
Enhance existing reporting processes and frameworks through automation and effective data management.
Apply AI and machine learning tools where appropriate to support reporting and investment decision-making.
Perform recurring and ad-hoc large-scale financial data analysis to generate actionable insights for business leaders.
Assess emerging technologies and innovative data solutions and evaluate their integration into existing systems.
Communicate complex and abstract concepts in clear, simple terms.
Create comprehensive documentation of current and target system architecture and code base.

Must Have Skills:

SQL proficiency (hands on for 5+ years)
Python proficiency (hands on for 5+ years)
Asset management/Investment industry knowledge or designation (highly preferred)
Proven experience in data analytics and machine learning is essential
Strong teamwork and cross-functional collaboration skills are critical

Nice to Have Skills:

C# advanced skills
PLSQL advanced skills
Snowflake experience
AWS experience
Hands-on experience with Streamlit, Prefect, Pydantic, NumPy, pandas, SQLAlchemy, and plotly
Data science and machine learning knowledge
Solid understanding and practical experience in capital markets
Familiarity with investment performance and risk analytics is strongly preferred
Masters, PhD, or CFA investment designation