détails d'emploi
Our client, is seeking an experienced, high-performing Senior QA Automation Engineer to join their Treasury and Balance Sheet Management technology group.
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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 GitHub 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 (GitHub 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, GitHub 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 ability to effectively utilize AI engineering tools (GitHub Copilot, Microsoft Copilot, agent-based workflows) to accelerate test automation, code design, and defect profiling.
Communication & Collaboration: Strong interpersonal skills with the ability to articulate technical risk, present test coverage, and collaborate effectively with both technical and non-technical partners.
Preferred Assets & Nice-to-Haves
Experience with Databricks notebooks, PySpark-based validation, Delta Lake quality checks, medallion/lakehouse architecture testing, and Spark SQL performance optimization.
Familiarity with data quality, observability, or CI/CD pipeline tools (e.g., Great Expectations, Deequ, dbt testing, Airflow, Azure DevOps, Jenkins).
Domain experience within Financial Services, Treasury, Capital Markets, Liquidity, Regulatory Reporting, or Balance Sheet Management.
Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical discipline.
Summary
If you are a tech-savvy Senior QA Automation Engineer who pairs 6+ years of test framework development with strong Python, SQL, Azure Databricks, and PySpark data validation skills, this 12-month hybrid contract in Toronto is an outstanding opportunity. Bring your data testing precision, AI-assisted engineering mindset, and collaborative approach to our client's treasury technology team today!
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
voir plus
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 GitHub 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 (GitHub 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, GitHub 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 ability to effectively utilize AI engineering tools (GitHub Copilot, Microsoft Copilot, agent-based workflows) to accelerate test automation, code design, and defect profiling.
Communication & Collaboration: Strong interpersonal skills with the ability to articulate technical risk, present test coverage, and collaborate effectively with both technical and non-technical partners.
Preferred Assets & Nice-to-Haves
Experience with Databricks notebooks, PySpark-based validation, Delta Lake quality checks, medallion/lakehouse architecture testing, and Spark SQL performance optimization.
Familiarity with data quality, observability, or CI/CD pipeline tools (e.g., Great Expectations, Deequ, dbt testing, Airflow, Azure DevOps, Jenkins).
Domain experience within Financial Services, Treasury, Capital Markets, Liquidity, Regulatory Reporting, or Balance Sheet Management.
Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical discipline.
Summary
If you are a tech-savvy Senior QA Automation Engineer who pairs 6+ years of test framework development with strong Python, SQL, Azure Databricks, and PySpark data validation skills, this 12-month hybrid contract in Toronto is an outstanding opportunity. Bring your data testing precision, AI-assisted engineering mindset, and collaborative approach to our client's treasury technology team today!
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.
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