Data Driven QA Automation Engineer

Riseup Labs; Vancouver, Calgary, Toronto; Híbrido; CAD 90.000 - 120.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Annual Performance Evaluation and Incr

Weekly 2 Holidays

Public Holidays as per Client Holiday

Descripción de la vacante

Riseup Labs is seeking a QA Engineer to own quality across data pipelines, platforms and applications. The role focuses on testing data pipelines in Snowflake with dbt, Python, and modern CI/CD practices.

You will design strategies, build automated tests, and collaborate with data engineers, platform engineers and product teams. Hybrid work from Canada with offices near Vancouver, Calgary or Toronto, 2 days in-office weekly.

Formación

• 4-6 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 comparable cloud data warehouse with quick ramp-up on Snowflake.
• Python for test automation and data validation scripts.
• dbt tests, or strong SQL and Python with dbt ramp-up within two weeks.
• Experience with a test automation framework: 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.
• Lives in Canada with valid work authorization, within 1 hour of Vancouver, Calgary or Toronto office, and able to work in the office 2 days a week.

Responsabilidades

• Design test strategies for data pipelines, validating accuracy, completeness, and schema consistency across ETL/ELT in Snowflake.
• Build automated data quality checks in dbt tests and Python, based on use cases and business requirements.
• Extend existing dbt and Python data quality tests.
• Build and maintain automated test suites (unit, integration, regression, end-to-end) for applications.
• Validate orchestration workflows in Airflow or Dagster for correctness and failure handling.
• Add automated testing to CI/CD pipelines for fast, reliable feedback.
• Run exploratory and manual testing for edge cases not yet covered by automation.
• Collaborate with data engineers to define and enforce data contracts and schema validation.
• Build and monitor quality dashboards (test coverage, defect trends, pipeline reliability) in Datadog (Grafana acceptable).
• Participate in root cause analysis for production incidents and close gaps in test coverage.
• Agree acceptance criteria and quality gates with engineering, product and analytics teams.
• Maintain clear test plans, test cases, defect reports and regression suites.

Conocimientos

QA/Test engineering

SQL queries

Data pipelines

English fluency

Analytical skills

Herramientas

Snowflake

dbt

Python

Pytest

Selenium

Cypress

Playwright

Jenkins

GitLab CI

CircleCI

Airflow

Dagster

Great Expectations

Soda Core

Descripción del empleo

Job Type: Full time No. of Vacancies: 1 Experience: 4 - 6 Years

Riseup Labs is seeking a QA Engineer ( who lives in Canada near at Vancouver, Calgary or Toronto ) to own quality across their data pipelines, platforms and applications. The data stack includes Snowflake, SQL, dbt, AWS or Azure, and Airflow or Dagster. Some standard tests already exist (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 work closely with data engineers, platform engineers, the project manager and other development squads to build a quality-first delivery culture.

Job 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 use cases and business requirements, and run them inside pipeline CI/CD.
• Extend the dbt and Python data quality tests 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 not yet covered by automation.
• 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 is acceptable, but Datadog is preferred.
• Take part in root cause analysis for production incidents and close gaps in test coverage.
• Agree acceptance criteria and quality gates with engineering, product and analytics teams.
• Maintain clear test plans, test cases, defect reports and regression suites.

Requirements:

• 4-6 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 the ability to ramp up on dbt within the first two weeks.
• Experience with a test automation framework: 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.
• Lives in Canada with valid work authorization, within 1 hour of the Vancouver, Calgary or Toronto office, and able to work in the office 2 days a week. Travel expenses are not covered.

Additional Requirements:

• Airflow or Dagster experience
• Great Expectations or Soda Core
• Data contract and schema validation experience
• Experience in a financial institution or other regulated environment
• Quality-first mindset: raises risks early without waiting to be asked.
• Works well with data engineers, platform engineers, product managers and other squads.
• Builds test cases from business requirements without needing every detail spelled out.
• Writes clear documentation others can reuse.
• Makes sound decisions independently and explains the reasoning.
• Handles sensitive data carefully.

Workplace :

• Hybrid (2 days a week on office)

Working Hours:

• 09.00 AM to 06.00 PM (Pacific, Mountain or Eastern)
• Negotiable (Based on experience and skills)

Compensation & Other Benefits (Applicable for International Candidate):

• Annual Performance Evaluation and Increment
• Weekly 2 Holidays
• Public Holidays as per Client Holiday Calendar

NB: Only shortlisted candidates will be communicated in the recruitment process.