Senior QA Automation Engineer (6+ years of experience) to build and evolve quality-control frameworks using Python, Selenium, PyTest, Azure Databricks, and Spark SQL 58522
Summary
This role involves building and maintaining automated quality-control frameworks for data pipelines and cloud-based analytics platforms within a financial services environment. The engineer will utilize Python, Selenium, PyTest, Azure Databricks, and Spark SQL to perform data validation and API testing.
Senior QA Automation Engineer (6+ years of experience) to build and evolve quality-control frameworks using Python, Selenium, PyTest, Azure Databricks, and Spark SQL 58522
Our financial services client is seeking a Senior QA Automation Engineer (6+ years of experience) to build and evolve quality-control frameworks using Python, Selenium, PyTest, Azure Databricks, and Spark SQL
Join a treasury and balance sheet management technology team supporting complex data movement, cloud-based analytics platforms, and enterprise data validation initiatives. This role focuses on QA automation, reusable testing frameworks, API validation, and large-volume data quality controls across Azure-based data platforms. The position offers exposure to high-volume integration projects within a banking environment and long-term contract potential.
Contract, Toronto, Hybrid, 4 days per week on site
79 Wellington Street
1 year
Must Haves
- 6+ years in QA automation, test framework development, and testing complex data platforms or application platforms
- Python, Perl, reusable automation frameworks, and validation utilities
- Selenium, PyTest, API testing, regression testing, and functional testing
- SQL, data validation, data reconciliation, schema validation, and large-volume data movement testing
- Azure Databricks, Spark SQL, Delta Lake, PySpark, Azure Data Factory, and university degree in Computer Science, Math, Engineering, or related field
Nice to Have
- Databricks notebooks, PySpark-based validation, and Delta Lake quality checks
- Medallion or lakehouse architecture testing and performance-aware Spark SQL test design
- Great Expectations, Deequ, DBT tests, Airflow, Azure DevOps pipelines, or Jenkins
- Financial services, treasury, capital markets, liquidity, regulatory reporting, or balance sheet management experience
- Test documentation, traceability, defect summaries, control evidence, and audit-ready validation artifacts
Responsibilities
- Design, develop, and maintain automated testing frameworks for data pipelines, APIs, cloud data platforms, and application workflows
- Create automated controls for completeness, accuracy, reconciliation, schema validation, anomaly detection, and data quality checks
- Develop and execute test strategies for Azure-based data solutions including Azure Databricks, Spark SQL, Delta Lake, and Azure Data Factory
- Build automated validation for REST APIs, service integrations, data ingestion, and downstream outputs
- Collaborate with testing leads, business users, BSAs, developers, and platform engineers to define test coverage and support delivery
- Apply Microsoft Copilot, GitHub Copilot, and agent-based workflows to support test generation, automation development, documentation, and defect analysis
Disclaimer: AI may be used in evaluating candidates.
This posting is for an existing vacancy.