Data Engineer - 78999

Position Title: ETF Systems Engineer

Line of business: Wealth Management / Global Asset Management / Analytics and Business Intelligence

Duration: 12 months (Possibility of Extension)

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

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 the bank's Global Asset Management. 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.

Team Structure: The selected candidate will be working in a collaborative environment within a team of approx. 5 people. This team is part of a larger 25 person GAM team.

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.

• Build strong internal and external relationships, working across teams to achieve business goals.

• Stay ahead of industry trends and proactively implement relevant changes.

• Take on additional responsibilities as needed to support broader business objectives.

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

Interviews:

Round 1: over Teams w/ hiring manager and team members (includes use case questions, theoretical questions, coding exercise)

Round 2: ideally meet in person (if possible) w/ hiring manager and senior manager

Round 3: If needed to make final decision