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ஒரு

QE Engineer

Aarorn Technologies Inc

Toronto, Ontario, Canada ஒப்பந்தம்

முதல் ஆளாக விண்ணப்பிக்கவும்

அனுபவம்
ஏதேனும்
சம்பளம்
CAD 45 – CAD 50 / hour
காலியிடங்கள்
1
பதிவுசெய்யப்பட்டது
1 மணி நேரம் முன்
Work mode
அலுவலகத்தில்
Eligibility
Candidates who can work on a contract basis in Toronto, Ontario, and attend onsite work four days per week, including an in-person interview, are eligible to apply.
Resume
Required to apply

Where you'll work

பணி விளக்கம்

Overview

Aarorn Technologies Inc is hiring a QE Engineer for a contract assignment in Toronto, Ontario. The role is based onsite four days per week and requires participation in an in-person interview process.

Role details

  • Location: Toronto, ON, with onsite attendance expected 4 times a week
  • Employment type: Contract
  • Interview format: Face-to-face, onsite only
  • Pay rate: CAD 45 to 50 per hour, inclusive

What you will do

  • Create, enhance, and support automation frameworks and monitoring tools for ETL workflows and data pipelines.
  • Develop data validation controls that catch issues early, before they affect downstream applications.
  • Analyze pipeline behavior and data outputs to uncover defects, irregularities, and improvement opportunities.
  • Build dashboards and reporting solutions to track data quality and pipeline health.
  • Coach junior and mid-level team members on quality engineering practices, test automation, analytics, and testing methods.
  • Improve CI/CD pipelines so that validation, testing, and deployment can run continuously and reliably.
  • Work closely with business teams, data analysts, and platform groups to define and enforce data quality expectations.
  • Investigate failures, resolve data-related issues, and tune processes for stronger reliability and performance.
  • Review code and audit automated tests to confirm standards and best practices are being followed.
  • Document frameworks, test approaches, analytics methods, and QE workflows for shared team use.
  • Contribute to architecture discussions where data quality, automation, and insights are key priorities.

Additional information

An AI-assisted screening or recruitment process may be used, but final hiring decisions remain with the recruitment team after a full evaluation of candidates.

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