Senior QA Specialist

As a Senior QA Specialist at our Toronto office, your key responsibilities will include testing ETL processes, APIs, and data pipelines to ensure data accuracy and integrity. You’ll also develop and maintain both automated and manual test cases for backend systems and reporting tools, collaborate with teams to identify and resolve issues, and write complex SQL queries to support thorough testing scenarios.

To succeed as a Senior QA Specialist, you should have at least 3 years of experience in QA, particularly for ETL processes and backend systems. Proficiency with ETL tools like Informatica or SSIS is essential, along with advanced SQL skills and experience in API testing. Strong communication and teamwork skills are also crucial for collaborating effectively within diverse teams.

The Senior QA Specialist plays a vital role in maintaining data integrity by implementing strategies that monitor and validate data continuously. You'll proactively identify and mitigate QA risks, ensuring that deliverables meet the specified functional, design, and business requirements, thus securing the quality of our data pipelines and reporting systems.

In this role, you'll work with various ETL tools, such as Informatica and SSIS, to ensure data quality and validation. You'll also employ SQL for writing and optimizing complex queries, and tools for API testing (SOAP/REST). Familiarity with cloud platforms like AWS and RDBMS such as SQL Server or PostgreSQL is a nice bonus!

As a Senior QA Specialist, you can expect to work on exciting and complex projects involving large financial datasets. You'll be testing data pipelines, validating dashboards and reports, and collaborating across teams to improve our reporting systems and operational workflows, making a significant impact on the quality and reliability of our data.

When discussing your experience with ETL testing, emphasize specific projects where you have successfully validated data movements between systems. Describe the tools you used and the methodologies you employed to ensure data accuracy throughout the processes.

To effectively answer this question, talk about your strategy for writing SQL queries, such as understanding the data structure and defining clear goals. Mention how you optimize queries for performance and the importance of thorough testing in various scenarios.

Provide examples of automated testing frameworks you have implemented, detailing the context of each project. Highlight the outcomes of using these frameworks, such as improved efficiency and reduced errors in your testing processes.

Discuss strategies you use for managing time effectively under pressure, such as prioritizing tasks, utilizing collaboration tools, and breaking down projects into manageable parts. Highlight a real-life experience where you met a tight deadline successfully.

Explain your risk assessment process, including how you analyze potential issues and develop mitigation strategies proactively. Share instances where you successfully identified risks before they escalated into larger problems.

Share your approach to fostering clear and open communication, whether through regular check-ins, detailed documentation, or tools that facilitate collaboration. Highlight a specific instance where good communication helped resolve an issue swiftly.

Discuss the significance of CI/CD in enhancing the efficiency and quality of the testing process. Share examples of how you have contributed to implementing best practices around CI/CD in your previous roles and the impact it had on project outcomes.

Detail your approach to validating dashboards and reports by focusing on the accuracy and integrity of data in visual presentations. Share tools you’ve used and any specific techniques that have proven effective in your validation processes.

Elaborate on your knowledge and hands-on experience with API testing, discussing the protocols you are familiar with (like SOAP or REST) and how you ensure the functionality and performance of APIs within your testing frameworks.

Discuss practices that you find effective for maintaining long-term data integrity, such as routine auditing, monitoring processes, and using automated testing tools. Provide an example of a project where these practices helped preserve data quality.