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Junior Python​/Data Engineer to vendor technology tool client in investment management industry

Job in Toronto, Ontario, M5A, Canada
Listing for: S.i. Systems
Contract position
Listed on 2026-02-12
Job specializations:
  • IT/Tech
    Data Engineer, Big Data
Job Description & How to Apply Below
Position: Junior Python/Data Engineer to support vendor technology tool for client in investment management industry

Contract: 3 Months + Extension

Hours: 37.5/HR

Work Model: 4 days in office

We support Murex
, a leading investment book of record (IBOR) platform that holds most of our critical financial data. Our data warehouse is hosted on AWS S3
, and we are building modern data pipelines to enable advanced data products and analytics across the organization.

You’ll join a collaborative team focused on data ingestion, integration and engineering
, working alongside experts in Java and vendor technologies. This role is ideal for someone who is skilled in Python
, passionate about data engineering, and eager to learn new technologies.

Key Responsibilities

  • Design and develop data pipelines to extract, transform, and load (ETL) data from Murex into AWS-based data platforms.
  • Build scalable and maintainable Python-based solutions for data ingestion and processing.
  • Collaborate with stakeholders to enable data products and analytics use cases.
  • Optimize data workflows for performance and reliability.
  • Troubleshoot and resolve data-related issues across systems.
  • Continuously learn and adapt to new tools, technologies, and best practices.
  • Required Skills & Experience

  • 3 years of experience in Python development with a focus on data engineering.
  • Strong understanding of ETL processes
    , data pipelines
    , and data modeling
    .
  • Experience with AWS services (S3, Lambda, Glue, or similar).
  • Familiarity with SQL and relational databases.
  • Ability to work in a collaborative environment and learn new technologies quickly.
  • Nice-to-Have

  • Exposure to Murex or other financial systems.
  • Experience with data orchestration tools (Airflow, Prefect).
  • Knowledge of big data frameworks (Spark, Hadoop).
  • Containerization
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