QE Engineer

Aarorn Technologies Inc; Toronto; On-site; CAD 61,992 - 68,880; Part time

Job summary

Aarorn Technologies Inc is seeking a QE Engineer based in Toronto, ON. This role involves developing and maintaining automated testing frameworks for data quality in pipelines, mentoring junior engineers, and ensuring high standards in data validation.

The ideal candidate will have experience in CI/CD practices, data analysis, and the ability to collaborate with business stakeholders across multiple teams.

Qualifications

• Experience in designing and maintaining automated testing frameworks.
• Strong background in data analysis and quality assurance.
• Familiarity with CI/CD practices for data validation.

Responsibilities

• Design and build automated testing frameworks for data pipelines.
• Perform in-depth data analysis and monitor data quality metrics.
• Mentor junior engineers on QE principles and testing strategies.

Tools

Automated Testing Frameworks

CI/CD Pipelines

Data Analysis

Job description

Job Title: QE Engineer

Location: Toronto, ON (4x onsite a week)

Employment Type: Contract

Pay Rate: CAD$45 - $50/HR INC

Interview Type: Face 2 Face (Onsite Interview Only)

Job Description

• Design, build, and maintain comprehensive automated testing frameworks and analytical monitoring solutions for data pipelines and ETL processes.
• Develop and deploy data quality validation frameworks that prevent data issues before they impact downstream systems.
• Perform in-depth data analysis to identify quality issues, anomalies, and optimization opportunities in data pipelines.
• Develop analytical dashboards and reports for monitoring data quality metrics and pipeline performance.
• Mentor and guide junior and mid-level engineers on QE principles, automation techniques, analytics, and testing strategies.
• Build and optimize CI/CD pipelines for continuous data validation, testing, and deployment.
• Collaborate with business stakeholders, data analysts, and platform teams to define, implement, and enforce data quality standards.
• Troubleshoot, diagnose, and optimize data processes with a focus on quality assurance, reliability, and performance.
• Conduct code reviews and automated testing audits to ensure quality standards are met.
• Document automation frameworks, testing strategies, analytics methodologies, and QE processes for team knowledge sharing.
• Participate in architectural decisions that prioritize data quality, automation capabilities, and analytical insights.