As a Senior QA Data Quality Engineer, you will lead quality assurance initiatives and collaborate with cross-functional technology teams to ensure the delivery of scalable, high-performance applications and platforms. The candidate will be responsible for building and maintaining automated test solutions to ensure high-quality software delivery.

This is a technical, delivery-focused role requiring an understanding of modern automation practices, the ability to leverage AI-assisted development tools, and a commitment to maintaining high quality standards within complex data environments.

In this role, you will

Responsible for overall quality of testing deliverables/activities.

Execute complex data validation strategies, focusing on Snowflake or SQL-based data integrity.

Develop and maintain basic Python scripts to automate testing tasks and streamline regression cycles.

Integrate and manage automated workflows within CI/CD pipelines.

Collaborate with technical teams to troubleshoot data discrepancies and ensure the robustness of the data ecosystem.

Responsible for designing effective test cases to bring test optimization.

Leverages the existing automation frameworks, tools and artifacts to ensure the testing process is continuous, comprehensive, and fully autonomous.

Support the implementation of the QE Program and overall QE process and standards through continuous test execution and reporting.

Closely work with the Application Development team as one team to integrate quality engineering mindset/concepts within the DevOps framework/pipeline.

Required skills

Overall 6-10 years of experience in Python, Javascript, SQL and Unix testing platform, code reviews prior to code deployments, integration test automation.

Automation & Scripting : Ability to create and update automation scripts using Python.

Database Testing: Strong expertise in DB testing, specifically using Snowflake or advanced SQL.

CI/CD Integration: Experience working with Airflow, Jenkins, or similar orchestration tools.

QE SDLC: Good understanding of the full QE SDLC, including requirements gathering, test case/scenario creation, execution, and formal documentation.

AI Integration: Practical exposure to using AI tools like Copilot or Cortex AI for code generation and efficiency.

Preferred skills

Experience with regulatory reporting projects and/or financial services industry.

QTest or any other defect management tool

Experience working in Unix environments

We're eager to meet people who share our mission and can make an impact in various ways. Don't hesitate to apply, even if you only meet the required skills listed. Your transferable skills and experiences matter—help us see how you the right person for this role.

Working arrangements

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements , this is a hybrid position requiring 4 days a week in a client or Cognizant office in Halifax, NS . Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you’re engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

Cognizant will only consider applicants for this position who are legally authorized to work in Canada without requiring employer sponsorship, now or at any time in the future.

Applications for this position are reviewed by our recruitment team without the use of artificial intelligence screening tools.