Senior QA Automation Engineer

Robertson & Company Ltd.; Toronto; Hybrid; CAD 87,000 - 117,000; Full time

Job summary

Robertson & Company Ltd. invites applications for a Senior QA Automation Engineer to join our client in Toronto, a hybrid role supporting data pipelines, APIs, and cloud data platforms.

You will design and maintain automated testing frameworks using Selenium, PyTest, and Python, and ensure data quality across large-scale movements and integrations. The position requires 6–10+ years in QA automation, strong SQL skills, Azure-based experience, and the ability to collaborate with business users,

Qualifications

• University degree required.
• 6–10+ years of experience in QA automation, test framework development, and testing of complex data or application platforms.
• Strong programming experience with Python, Perl, or a similar scripting language.
• 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.
• 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.
• Computer Science, Engineering, Information Systems, or a related technical degree or equivalent practical experience.

Responsibilities

• 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
• Test data movement across systems by creating automated controls for completeness, accuracy, reconciliation, schema validation, anomaly detection, and quality checks at key integration points
• 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
• Build automated validation for REST APIs, service integrations, data ingestion, and downstream outputs using fit-for-purpose tools and frameworks
• 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
• 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
• Strong technical depth, practical testing judgment, and a continuous-improvement mindset

Skills

QA automation

Test frameworks

Python scripting

SQL validation

Azure data

AI tools

Big data

Data quality

Collaboration

Communication

Education

University degree

Tools

Selenium

PyTest

Python

Job description

Our client is a top financial institution with significant North American holdings. They have operations across most major verticals, including institutional & corporate, wealth management, private clients, commercial banking, treasury, and retail banking.

Introduction

Robertson is seeking a skilled Senior QA Automation Engineer to join our client in support of an existing vacancy.

Contract Period

12 months with potential to extend or convert

Pay Rate

Starting form $74 per hour

Location

Toronto, ON

Location Type

Hybrid

Business Hours

Monday-Friday, Core business hours

Job Responsibilities

• 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
• Test data movement across systems by creating automated controls for completeness, accuracy, reconciliation, schema validation, anomaly detection, and quality checks at key integration points
• 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
• Build automated validation for REST APIs, service integrations, data ingestion, and downstream outputs using fit-for-purpose tools and frameworks
• 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
• 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
• Strong technical depth, practical testing judgment, and a continuous-improvement mindset

Experience & Qualification Requirements

• University degree required
• 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
• 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
• Computer Science, Engineering, Information Systems, or a related technical degree or equivalent practical experience

Background screening is required as part of the onboarding process. The type of screening required (criminal, credit, or other verifications) will vary based on the position and client requirements.

We use AI technology as part of our application review process to assist with screening and assessment. All applications are also reviewed by our recruitment team.

Robertson & the clients we represent are equal opportunity employers, committed to diversity and inclusion. Robertson is a certified diverse supplier and actively seeks to foster a representative and inclusive workforce. We welcome applications from all qualified individuals, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, Aboriginal status, or any other legally protected factors. We champion building a diverse and inclusive environment.