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.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外，候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
Cognizant 是一家提供平等就业机会的雇主。在招聘过程中，您的申请和候选资格不会因种族、肤色、性别、宗教、信仰、性取向、性别认同、国籍、残疾、遗传信息、怀孕、退伍军人身份或任何其他受联邦、州或地方法律保护的特征而受到影响。
