Senior Data QA – Datalinx (Back‑end Engineering)
We are looking for a technical Senior Data QA to join our Datalinx cluster. This is a backend‑heavy engineering role focused on high‑volume trade simulation and data integrity. You will use Python to build automation frameworks that simulate thousands of real‑time trades, ensuring our systems can handle market volatility. You will use complex SQL to deep‑dive into our databases, validating that every byte of data flowing through our AWS pipelines is accurate, compliant, and timely.

Reports to: Senior Manager, Data & Analytics & Enterprise Data Architect

Job Location: Hybrid (2‑3 days in office) – based in Toronto, ON.

Key Accountabilities

Build Simulation Frameworks: Design and maintain Python‑based automation scripts (using Pytest/Requests) to simulate thousands of real‑time trades and stress‑test our trading platforms.

Data Pipeline Validation: Validate ETL/ELT processes within AWS. Ensure data flows correctly from ingestion to storage, identifying data loss or transformation errors.

Deep‑Dive Analysis: Execute advanced SQL queries against MySQL/Snowflake/Hive databases to verify data accuracy, consistency, and completeness across the Datalinx ecosystem.

Performance Engineering: Identify bottlenecks in the data product lifecycle. Analyze how the system behaves under high load and work with developers to optimize performance.

Root Cause Analysis: Go beyond “reporting bugs.” Trace issues back to the specific service, API endpoint, or database procedure causing the failure.

The Tech Stack

Language: Python (Heavy scripting, Pytest, Pandas, Requests).

Database: SQL (MySQL, Snowflake, Hive, Athena).

Cloud: AWS (S3, Data Pipelines, EC2, EMR, Lambda functions, REST APIs).

Tools: GitHub, JIRA, Confluence.

Must Haves





5+ years in Software Quality Assurance with a specific focus on Data QA and Backend Automation.

Python Expertise: You can write Python code from scratch to generate test data, mock APIs, and simulate user traffic.

Advanced SQL Skills: You can write complex joins and window functions to validate large datasets without relying on a GUI.

AWS & Cloud Data: Proven experience testing data pipelines and understanding how data moves through cloud infrastructure (AWS preferred).

API Testing: Robust experience testing RESTful APIs and integrating them into automation suites.

Performance Testing: Experience with load testing tools and strategies (simulating high‑volume transactions).Operational Support: Support releases during off‑business hours, when planned. Also provide support in case of adhoc issues to ensure system reliability.

Nice To Haves

Capital Markets Experience: Understanding of equity markets, trade lifecycles, and financial instruments.

Big Data Tech: Experience with Hadoop, Spark, or Hive.

Shell Scripting: Working knowledge of shell scripting in a Linux environment.

Salary Range: 100,000 /year – 120,000 /year CAD. Please note that the salary range included is a guideline only. The salary offered may vary based on factors, including, but not limited to, the successful candidate’s relevant knowledge, skills, and experience.

Please note that our company is not currently sponsoring work permit applications and the applicant must be authorized to work in the country where this position is located.

TMX is committed to creating and sustaining a collegial work environment in which all individuals are treated with dignity and respect and one which reflects the diversity of the community in which we operate. We provide accommodations for applicants and employees who require it.

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📌 Senior Data QA Analyst (Ontario)
🏢 TMX Group
📍 Ontario