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Hays

Quality Engineer

Toronto, ON, Canada

Hourly Pay: $65/hr to $80/hr · Contract

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Job details

Pay: Hourly Pay: $65/hr to $80/hr
Job type: Contract
Apply by: Nov 4, 2026
Posting language: English
Posted: Oct 5, 2026

Original job description

Hourly Pay: $65/hr to $80/hr

Your New Company

A leading organization is seeking a highly skilled and experienced Senior Quality Engineer to join its Enterprise Technology and Data team. This role is focused on ensuring the delivery of high-quality data-driven solutions and applications across enterprise systems, supporting large-scale data platforms and cloud-based technologies.

Your New Role

As a Senior Quality Engineer, you will be responsible for defining and implementing quality assurance processes, developing automated tests, identifying and mitigating risks, and ensuring the overall quality of technology and data platforms across multi-cloud environments (Azure and Google Cloud Platform). You will work closely with developers, data engineers, product managers, and business stakeholders to maintain the highest quality standards throughout the software development lifecycle.

Main Activities:

Design detailed test strategies/plans, test cases, and test scripts to validate data accuracy, integrity, and system functionality in ETL pipelines across Azure and GCP, including both functional and non-functional testing.
Collaborate with data engineers to monitor and ensure the accuracy, completeness, and consistency of data across Azure Synapse/Fabric and Google BigQuery, validating transformations and data integrity in ETL pipelines.
Collaborate with data engineering teams to design and execute tests for data pipelines running on Azure Fabric and Google Cloud services such as Dataflow, Dataproc, and Pub/Sub-based pipelines.
Develop and execute SQL-based automated tests for database validation, ensuring data integrity, performance, and security across BigQuery datasets and Azure SQL/Synapse environments.
Conduct performance testing to evaluate the scalability, stability, and performance of large-scale data systems across Azure and GCP.
Develop and maintain automated testing frameworks for ETL processes, APIs, and data integration systems, extending automation to support BigQuery validation, GCP pipeline testing, and AI/ML data validation scenarios.
Work with development and operations teams to identify, report, and track defects across multi-cloud data ecosystems, ensuring timely resolution.
Propose and implement improvements to testing processes and frameworks across Azure and Google Cloud-based data platforms and AI-enabled data solutions.
Partner with business stakeholders, project managers, and technical teams to ensure alignment with quality goals and deliverables.
Provide mentorship and technical guidance to junior quality engineers in cloud-native and AI-driven validation practices.
Ensure adherence to industry standards and best practices related to software quality, ETL processes, and cloud technologies.

What You'll Need to Succeed:

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.

Experience

5+ years of experience in software quality engineering.
Minimum 3 years of experience working in an enterprise data environment.
Proven experience with automated testing tools such as Selenium, JUnit, TestNG, or similar frameworks.
Hands-on experience with data validation, transformation, and data pipeline testing in Azure and/or Google Cloud Platform environments.
Strong understanding of data management, data warehousing, ETL processes, and data integration.
Experience with Azure Data Factory, Azure Synapse, Microsoft Fabric, Google BigQuery, Dataflow, Dataproc, and cloud-based ETL tools is considered an asset.

Technical Skills

Proficiency in Python, Java, and SQL for test automation and ETL validation.
Experience working with Azure Data Factory, Azure Synapse Analytics, Microsoft Fabric, BigQuery, Dataflow, and Cloud Composer (Airflow).
Strong knowledge of Agile, Scrum, Waterfall methodologies and CI/CD environments.
Experience with Git, Jenkins, Azure DevOps, Azure, and GCP infrastructure.

Soft Skills

Strong analytical, troubleshooting, and problem-solving abilities.
Excellent communication and collaboration skills.
Detail-oriented with a focus on quality and accuracy.
Ability to work independently while managing multiple priorities in a fast-paced environment.

Nice to Have

Azure DevOps, Azure ML, ISTQB, Google Cloud Professional Data Engineer, or Professional Cloud Developer certifications.
Experience with data governance tools such as Azure Purview and data compliance initiatives.

What You'll Get in Return:

You will have the opportunity to work with a talented team of professionals in a dynamic and supportive environment. The organization offers competitive compensation, professional development opportunities, and the chance to make a significant impact on enterprise technology and data initiatives.

What You Need to Do

Interested candidates should apply with an updated resume highlighting their experience in Quality Engineering, ETL Testing, Data Validation, Azure, Google Cloud Platform, and test automation frameworks.

What You Need to Do Now:

If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.

If this job isn't quite right for you, but you are looking for a new position, please contact us for a confidential discussion on your career.

This posting is for an existing vacancy with the organization.

AI may be used to screen, assess or select applicants for the position.

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More about this job

Responsibilities

Define and implement quality assurance strategies, automated tests, and data validation processes for enterprise data platforms and ETL pipelines across Azure and Google Cloud. Identify and track defects, improve testing frameworks, collaborate with technical and business teams, and mentor junior quality engineers.

Requirements

Requires a bachelor's degree in a relevant field, at least five years of software quality engineering experience, and at least three years in an enterprise data environment. Candidates should have experience with test automation, cloud data pipelines, ETL and data validation, and proficiency in Python, Java, and SQL.

Skills

Quality Engineering
Test Automation
ETL Testing
Data Validation
SQL
Python
Java
Azure
Google Cloud Platform
BigQuery
Azure Synapse
Microsoft Fabric
Azure Data Factory
Performance Testing
CI/CD
Agile

Benefits

Competitive Compensation
Professional Development Opportunities

Visa sponsorship

Not detected in the job text

Keywords

Quality Engineering
Quality Assurance
Test Automation
Selenium
JUnit
TestNG
ETL
Data Validation
Data Warehousing
Data Integration
Python
Java
SQL
Azure Data Factory
Azure Synapse Analytics
Microsoft Fabric
Google BigQuery
Google Cloud Platform
Dataflow
Dataproc
Cloud Composer
Apache Airflow
Azure DevOps
Jenkins
Git
CI/CD
Agile
Scrum
Waterfall
Performance Testing

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