ETL QA Engineer
We are seeking an experienced ETL QA Engineer with 69 years of professional experience to join our team in Toronto, Canada.
This role is critical to ensuring the accuracy, reliability, and performance of enterprise data pipelines and cloud based data solutions.
The ETL QA Engineer will be responsible for validating complex data transformations, automating test processes, and ensuring that data systems meet business requirements for analytics, reporting, and compliance.
By safeguarding the integrity of data across multiple platforms, this role enables the organization to make confident, data driven decisions and supports strategic growth initiatives.
Design and implement automated testing frameworks to validate data quality, transformations, and integrations.
Collaborate with data engineers, analysts, and business stakeholders to understand requirements and translate them into test scenarios.
Perform functional, regression, and performance testing of data workflows to ensure reliability and scalability.
Validate data migration and integration between on‑premise and cloud environments.
Monitor and report on data quality issues, ensuring timely resolution and root‑cause analysis.
Document test cases, results, and processes to maintain transparency and knowledge sharing.
Support continuous improvement by identifying gaps in testing processes and recommending enhancements.
We are seeking an experienced ETL QA Engineer with 69 years of professional experience to join our team in Toronto, Canada.
This role is critical to ensuring the accuracy, reliability, and performance of enterprise data pipelines and cloud based data solutions.
The ETL QA Engineer will be responsible for validating complex data transformations, automating test processes, and ensuring that data systems meet business requirements for analytics, reporting, and compliance.
By safeguarding the integrity of data across multiple platforms, this role enables the organization to make confident, data driven decisions and supports strategic growth initiatives.
Design and implement automated testing frameworks to validate data quality, transformations, and integrations.
Collaborate with data engineers, analysts, and business stakeholders to understand requirements and translate them into test scenarios.
Perform functional, regression, and performance testing of data workflows to ensure reliability and scalability.
Validate data migration and integration between on‑premise and cloud environments.
Monitor and report on data quality issues, ensuring timely resolution and root‑cause analysis.
Document test cases, results, and processes to maintain transparency and knowledge sharing.
Support continuous improvement by identifying gaps in testing processes and recommending enhancements.