Senior Qa

Location:- Montreal (Remote)/ Toronto (Hybrid-3 days onsite)
Duration:- Long term contract
Must have :- English and French language skills must
Job DescriptionWe are looking for a technical Senior QA. 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.
If you enjoy breaking data pipelines, automating complex scenarios, and working in a high-stakes trading environment, this is the role for you.
Key Responsibilities
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 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
Database: SQL (MySQL, Snowflake, Hive, Athena).
Cloud: AWS (S3, Data Pipelines, EC2, EMR, Lambda functions, REST APIs).
Must-Have Qualifications
5+ years in Software Quality Assurance with a specific focus on Data QA and Backend Automation.
Python Expertise: You aren't just running scripts;
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: Strong 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 providing 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.
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