Prestador De Servicios

Cliente: Outforce
QA Engineer, Data

ABOUT THE ROLE
The company needs a QA Engineer to own quality across its data pipelines, platforms and applications. The data stack includes Snowflake, SQL, dbt, AWS or Azure, and Airflow or Dagster. Some standard tests already exist, including dbt tests and Python data quality checks. Most of the work is building new tests for specific use cases and business requirements. You will design testing strategies that catch issues before production, and you will work with PTC data engineers, platform engineers, the project manager and other development squads to build a quality-first delivery culture.

Advanced English is required

ROLE DETAILS

• Role: QA Engineer, Data
• Location: Canada. Hybrid, 2 days per week in office in Vancouver, Calgary or Toronto. Candidates must live within commuting distance of one of these offices and have a work permit.
• Working hours: Standard business hours in the candidate's local time zone. Pacific, Mountain and Eastern are all acceptable.
• Experience Level: 4 to 6 years in QA or test engineering, mid-level to senior

RESPONSIBILITIES

• Design test strategies for data pipelines, validating accuracy, completeness, schema consistency and transformation logic across ETL and ELT workflows in Snowflake.
• Build new automated data quality checks in dbt tests and Python, based on specific use cases and business requirements, and run them inside pipeline CI/CD.
• Extend the existing dbt and Python data quality tests that are already in place.
• Build and maintain automated test suites (unit, integration, regression and end-to-end) for applications.
• Validate orchestration workflows in Airflow or Dagster for correctness, idempotency and failure handling.
• Add automated testing to CI/CD pipelines for fast, reliable feedback.
• Run exploratory and manual testing for edge cases that automation does not cover yet.
• Work with data engineers to define and enforce data contracts and schema validation between upstream and downstream systems.
• Build and monitor quality dashboards (test coverage, defect trends, pipeline reliability) in Datadog. Grafana experience is acceptable, but Datadog is preferred.
• Join root cause analysis for production incidents and close the gaps in test coverage.
• Work with engineering, product and analytics teams to set acceptance criteria and quality gates.
• Keep clear test plans, test cases, defect reports and regression suites.

WHAT WE NEED TO SEE IN CANDIDATES
Have to have

• 4 to 6 years in QA or test engineering, with hands-on data pipeline or ETL testing.
• Strong SQL for data validation and query-based testing.
• Snowflake, or a comparable cloud data warehouse with a clear ability to ramp up on Snowflake quickly.
• Python for test automation and data validation scripts.
• dbt tests, or strong SQL and Python with a clear ability to ramp up on dbt in the first two weeks.
• Test automation framework experience: Pytest, Selenium, Cypress, Playwright or similar.
• CI/CD integration of automated tests: Jenkins, GitLab CI, CircleCI or similar.
• Working awareness of data privacy, security and PII handling.
• Strong analytical and troubleshooting skills with close attention to detail.
• Clear spoken and written English for daily work with data engineers, the project manager and development squads.
• Lives in Canada and can work 2 days per week in office in Vancouver, Calgary or Toronto.

Nice to have

• Airflow or Dagster experience, since both are in the PTC stack.
• AWS or Azure experience.
• Datadog dashboards (preferred). Grafana is also acceptable.
• Great Expectations or Soda Core. These are not in use at PTC today.
• Data contract and schema validation experience.
• Experience in a financial institution or other regulated environment.