Senior QA Automation Engineer

Our client, is seeking an experienced, high-performing Senior QA Automation Engineer to join their Treasury and Balance Sheet Management technology group.

In this high-impact quality engineering role, you will help build and evolve enterprise quality-control frameworks for complex data movement, large-volume data validation, and cloud-based analytics platforms. You will combine strong automation engineering skills, hands-on data testing depth, and an AI-forward mindset—leveraging tools like Git Hub Copilot, Microsoft Copilot, and agent-based workflows responsibly to accelerate quality outcomes. Working alongside business systems analysts, data engineers, and platform leads, you will design automated controls, test Azure-based lakehouse architectures (Databricks, PySpark, Delta Lake), validate REST APIs, and enforce audit-ready data reconciliation standards.

Duration: 12-Month Contract (with high potential for extension or permanent conversion)

Location & Work Arrangement:
Toronto, ON (Hybrid: 4 days per week on-site at the corporate office)

Advantages
High-Impact Financial Platform Scope:
Direct quality engineering and automated controls for mission-critical enterprise treasury, liquidity, and regulatory data systems.

Competitive Hourly Rate:
Attractive compensation ranging from $115/hr to $130/hr based on candidate technical depth.

Modern Cloud & AI Sandbox:
Build automated test suites across modern Azure Data Lakehouse architectures while utilizing AI-enabled tools (Git Hub Copilot, agentic workflows) to accelerate delivery.

Substantial Contract Duration:
Secure a full 12-month consulting engagement within a well-funded, stable financial technology group.

Responsibilities
Automation Framework Engineering:
Design, build, and maintain automated testing frameworks for cloud data pipelines, REST APIs, and application workflows using Python, Selenium, PyTest, and custom automation utilities.

Large-Volume Data Validation:
Test complex data pipelines by building automated quality controls for reconciliation, data completeness, schema validation, accuracy checks, and anomaly detection.

Cloud Data Platform Testing:
Develop and execute test strategies for Azure-based cloud data environments, including Azure Databricks, Spark SQL, Delta Lake, PySpark, ADLS, and Azure Data Factory orchestration.

API & Integration Testing:
Build automated validation suites for REST APIs, data ingestion endpoints, and downstream analytics reporting outputs.

AI-Enabled Efficiency:
Apply Microsoft Copilot, Git Hub Copilot, and agent-based workflows to accelerate test design, test case generation, defect analysis, and documentation while maintaining strict engineering review practices.

Cross-Functional Collaboration & Compliance:
Partner with business users, BSAs, developers, and platform leads to translate business requirements into audit-ready validation artifacts, defect summaries, and control evidence.

Qualifications
Technology & QA

Experience:

6 to 10+ years of overall software technology experience, including hands-on QA automation, test framework development, and testing complex data or application platforms.

Scripting & Automation Depth:
Strong programming proficiency in Python (or Perl/similar languages), with hands-on experience using Selenium, PyTest, and modern API testing frameworks.

SQL & Data Testing Mastery:
Advanced SQL skills and proven data validation experience testing large-volume data movement, source-to-target reconciliation, completeness, schema checks, and data quality rules.

Azure Cloud Data Ecosystem:
Practical experience with Azure data platforms, including Azure Databricks, Spark SQL, Delta Lake, PySpark, Azure Data Lake Storage (ADLS), and Azure Data Factory (ADF).

AI Tooling Proficiency:
Demonstrated…