ETF Systems Engineer at Procom
Toronto, ON, Canada -
Full Time


Start Date

Immediate

Expiry Date

03 Dec, 25

Salary

0.0

Posted On

03 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Analytics, Pandas, Sqlalchemy, Machine Learning, Numpy, Designation, Teamwork

Industry

Information Technology/IT

Description

ETF SYSTEMS ENGINEER:

On behalf of our Banking client, Procom is searching for an ETF Systems Engineer for a 12-month role. This position is a hybrid position with up to four days onsite at our client’s Toronto office.

ETF SYSTEMS ENGINEER - JOB DESCRIPTION:

The ETF Systems Engineer will be part of the analytics and business intelligence team, supporting the development and enhancement of ETF analytics systems at Global Asset Management. The role involves platform development across various asset classes, combining financial market expertise with advanced technology and data skills.

ETF SYSTEMS ENGINEER - MANDATORY SKILLS:

  • SQL proficiency with hands-on experience of 5+ years.
  • Python proficiency with hands-on experience of 5+ years.
  • Knowledge or designation in the asset management/investment industry is highly preferred.
  • Proven experience in data analytics and machine learning.
  • Strong abilities in teamwork and cross-functional collaboration.

ETF SYSTEMS ENGINEER – NICE-TO-HAVE SKILLS:

  • Experience with advanced C# and PLSQL skills.
  • Familiarity with Snowflake and AWS platforms.
  • Hands-on proficiency in tools such as Streamlit, Prefect, Pydantic, NumPy, pandas, SQLAlchemy, and plotly.
  • A relevant advanced degree (Masters, PhD) or a CFA investment designation would be advantageous.
Responsibilities
  • Collaborate with portfolio managers to enhance the technology platform for daily investment workflows.
  • Partner with Data Engineers and Business Analysts to design data pipelines and automate routine operations.
  • Support the redesign and migration of legacy investment analytics frameworks to modern infrastructure.
  • Automate existing reporting processes and improve data management frameworks.
  • Apply AI and machine learning tools to support reporting and investment decisions.
  • Conduct large-scale financial data analysis to derive actionable insights for leadership.
  • Assess and integrate emerging technologies and innovative data solutions into current systems.
Loading...