Senior QA Automation Engineer – Hybrid in Toronto

Location: Toronto, ON

Onsite Flexibility: Hybrid — four days per week onsite, with one remote day based on team and business needs

Contract Details:

• Position Type: Contract
• Contract Duration: 12 months
• Pay Rate: C$90.00–C$100.00 / Hour (CAD)
• Shift / Schedule: Core business hours
• Travel Requirements: Not required

Job Summary:

Treasury and Balance Sheet Management plays a critical role in supporting the bank's financial strength, data integrity, regulatory commitments, and operational resilience. Our technology teams partner closely with treasury business users, testing leads, business systems analysts, engineers, and platform teams to deliver trusted data solutions, modern testing practices, and controls that help strengthen decision-making across the enterprise.

As a Senior QA Automation Engineer, you will help build and evolve quality-control frameworks for complex data movement, large-volume data validation, and cloud-based analytics platforms. You will bring strong automation engineering experience, hands-on data testing skills, and the ability to use AI, Copilot, and agent-based workflows responsibly and effectively to accelerate quality engineering outcomes.

Key Responsibilities:

• Build confidence through automation: Design, develop, and maintain automated testing frameworks for data pipelines, APIs, cloud data platforms, and application workflows using tools such as Selenium, PyTest, Python, and related automation libraries.
• Validate data with precision: Test data movement across systems by creating automated controls for completeness, accuracy, reconciliation, schema validation, anomaly detection, and quality checks at key integration points.
• Support modern data platforms: Develop and execute test strategies for Azure-based data solutions, including Azure Databricks, Spark SQL, Delta Lake, PySpark, Azure Data Lake Storage, Azure Data Factory, and related data engineering pipelines.
• Strengthen API and integration testing: Build automated validation for REST APIs, service integrations, data ingestion, and downstream outputs using fit-for-purpose tools and frameworks.
• Partner across teams: Work with testing leads, treasury business users, business systems analysts, developers, and platform engineers to understand requirements, define test coverage, and support end-to-end delivery.
• Use AI responsibly to improve delivery: Apply Microsoft Copilot, GitHub Copilot, and agent-based workflows to support test generation, code acceleration, documentation, defect analysis, data profiling, and regression coverage while maintaining engineering judgment, review discipline, and compliance expectations.

Required Skills:

• 6–10 years of overall technology experience, including hands-on QA automation, test framework development, and testing of complex data or application platforms.
• Strong programming experience with Python, Perl, or a similar scripting language, with the ability to build reusable automation utilities and validation frameworks.
• Hands-on experience with Selenium, PyTest, API testing, regression testing, functional testing, and automated test execution in modern delivery environments.
• Strong SQL and data validation experience, including testing large-volume data movement, reconciliation, completeness, accuracy, schema checks, and data quality controls.
• Practical experience with Azure-based data platforms and services, including Azure Databricks, Spark SQL, Delta Lake, PySpark, Azure Data Lake Storage, Azure Data Factory, and related cloud data engineering patterns.
• Ability to use AI-enabled engineering tools effectively, including Microsoft Copilot, GitHub Copilot, and agent-based workflows, to accelerate test design, automation development, documentation, defect analysis, and productivity while applying responsible review and validation practices.
• Strong communication and collaboration skills, with the ability to work with business users, BSAs, developers, testing leads, and platform teams to translate requirements into clear test strategies and deliverables.

Preferred Skills:

• Experience with Databricks notebooks, PySpark-based validation, Delta Lake quality checks, medallion or lakehouse architecture testing, and performance-aware Spark SQL test design.
• Experience with data quality, observability, or orchestration tools such as Great Expectations, Deequ, DBT tests, Airflow, Azure DevOps pipelines, Jenkins, or similar frameworks.
• Financial services, treasury, capital markets, liquidity, regulatory reporting, or balance sheet management experience.
• Experience creating test documentation, traceability, defect summaries, control evidence, and audit-ready validation artifacts.

Education Requirements:

University degree in Computer Science, Math, Engineering, Information Systems, or a related technical field is ideal; equivalent practical experience accepted.

Required Experience:

Minimum 6 years (6–10 years) of overall technology experience, including hands-on QA automation, test framework development, and testing of complex data or application platforms.

Important Notes:

Interview process: 2 rounds of interviews.

About the Client:

This client is a leading financial services and banking institution operating across Canada and internationally, with technology teams embedded in critical functions including Treasury and Balance Sheet Management. The organization employs thousands of technology professionals — including QA automation engineers, data engineers, business systems analysts, solutions developers, and platform architects — who collaborate in agile, fast-paced environments to deliver trusted data solutions and regulatory-grade controls at enterprise scale.

About GTT:

GTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation, a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking, financial services, technology, life sciences, biotech, utilities, and retail sectors throughout the U.S. and Canada.