Senior Quality Engineer

Job summary

Test complex data pipelines and ETL/ELT workflows, including source-to-target validation, reconciliation, and transformation testing. Build automated data validation frameworks, test cloud data platforms, integrate tests into CI/CD pipelines, and troubleshoot data-quality issues with engineering teams.

Job details

Senior Quality Engineer – Data & Cloud Location: Toronto, ON – Hybrid, 1 day/week onsite Contract: 12 months to start Start: November 2026 We’re looking for a Senior Quality Engineer with strong experience in data quality, QA automation, and enterprise data platforms. This is a hands-on role focused on testing and validating complex ETL/ELT pipelines, building automated data validation frameworks, and ensuring data quality across modern cloud environments. What You’ll Do Test and validate complex data pipelines and ETL/ELT workflows Perform source-to-target validation, data reconciliation, and transformation testing Build automated testing frameworks using Python and SQL Test data platforms across Azure and/or GCP Work with technologies such as Microsoft Fabric, Synapse, Azure Data Factory, BigQuery, and Dataflow Perform API, integration, and performance testing Integrate automated testing into CI/CD pipelines Troubleshoot data-quality issues and work closely with engineering teams What We’re Looking For 7–12 years of QA / Quality Engineering experience 3–5+ years testing enterprise data platforms Strong SQL and Python Strong understanding of ETL/ELT, data warehousing, and data pipelines Experience with Azure and/or GCP Experience building automated testing or data validation frameworks Familiarity with Git, Azure DevOps, Jenkins, or similar CI/CD tools Nice to have: Microsoft Fabric, Azure Synapse, BigQuery, Dataflow, Airflow/Cloud Composer, data governance, or AI/ML data validation experience. This is a great fit for someone who understands how data moves, how transformations work, and how to identify and prevent data-quality issues through automation.

What you’ll do

Test complex data pipelines and ETL/ELT workflows, including source-to-target validation, reconciliation, and transformation testing. Build automated data validation frameworks, test cloud data platforms, integrate tests into CI/CD pipelines, and troubleshoot data-quality issues with engineering teams.

Requirements

Requires 7–12 years of QA or quality engineering experience, including 3–5 or more years testing enterprise data platforms. Candidates should have strong SQL and Python skills, knowledge of ETL/ELT and data warehousing, experience with Azure and/or GCP, and familiarity with automated testing frameworks and CI/CD tools.

Listed skills

• SQL · Preferred
• Python · Preferred
• Microsoft Azure · Preferred
• CI/CD · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Data Quality
• Quality Engineering
• QA Automation
• SQL
• Python
• ETL/ELT Testing
• Data Pipeline Testing
• Data Reconciliation
• Data Warehousing
• Azure
• Google Cloud Platform
• API Testing
• Integration Testing
• Performance Testing
• CI/CD
• Automated Data Validation

Job areas

• Technology
• Data & Analytics
• Software
• Engineering

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