Data QA Engineer - Remote
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Before you apply
LocationLahore, Punjab, Pakistan
Work moderemote
Typefull-time
SenioritySenior
Experience5+ yrs
DepartmentTech
Company size201–500 people
PostedOct 17, 2026 · 2w ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
5+ years in a QA Engineer or similar role
SQL: basic to intermediate queries
Solid grasp of web technologies: HTML, XPath, JSON, HTTP, CSS
Experience writing tests against HTTP/REST APIs
Proactive and detail-oriented QA professional
Fast learner adept at understanding complex domain requirements
Leveraging AI and LLM tools to optimize test case generation
Good test case design and test data management
Experience working in an agile team (Scrum or Kanban)
Understanding of data quality concepts such as completeness, accuracy, consistency, drift
Strong attention to detail and confidence to hold quality line
Clear written and spoken communication in English
Python preferred language
Pandas for data analysis and validation
Jupyter for data analysis and validation
Working knowledge of Scrapy and other Python-based scraping frameworks
Experience with test automation frameworks
Interest in data science concepts as they apply to data analysis and validation
Interest in using AI and LLM tools to speed up data validation
Skills
Python
Pandas
Jupyter
SQL
HTML
XPath
JSON
HTTP
CSS
REST APIs
AI
LLM
Scrapy
test automation frameworks
Benefits
Paid time off
Remote flexibility
About the company
At Zyte, we eat data for breakfast and you can eat your breakfast anywhere and work for Zyte. Founded in 2010, we are a globally distributed team of over 250 Zytans working from over 28 countries who are on a mission to enable our customers to extract the data they need to continue to innovate and grow their businesses. We believe that all businesses deserve a smooth pathway to data.
About the role
Role Overview
Data QA is how we make sure the data we deliver is right before the customer sees it. As a Data QA Engineer, you will check the data our spiders and AI-assisted projects produce against what the customer asked for, find what is wrong and tell the team exactly what you found.
Quality assurance is more useful as a question asked at the start than a gate at the end. Is this requirement testable and how would we know if it were wrong? Part of this role is asking that question early, so problems are fixed before they reach the customer.
Responsibilities
Key Responsibilities
•
Turn customer scraping and data requirements into a clear test approach and own QA from the start on new projects.
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Combine exploratory manual and visual testing with automated tests where automation pays for itself.
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Run test cycles on extracted data and report the results clearly.
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Write up defects with enough detail that a developer can reproduce and fix them without a conversation.
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Use descriptive statistics, summaries and charts to show how good the data is: completeness, accuracy, consistency and drift.
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Produce test reports and quality scores that give the team, and the customer where needed, a true picture.
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Say what was tested, what was not, and what risk that leaves.
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Work with project managers and clients to clear up unclear or untestable requirements before QA begins.
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Feed into our test automation framework, with a focus on coverage and performance.
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Suggest and take ownership of improvements to QA process and tooling, including browser add-ons, spreadsheet add-ons and UI-based test automation tools.
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Work with QA leadership, project managers and developers, with minimal supervision.
Requirements
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5+ years in a QA Engineer or similar role - testing software or data.
•
Python preferred language - Pandas and Jupyter for data analysis and validation.
•
SQL: basic to intermediate queries, and comfort with at least one relational database and its tools.
•
A solid grasp of web technologies and protocols: HTML, XPath, JSON, HTTP and CSS.
•
Experience writing tests against HTTP/REST APIs.
•
Proactive and detail-oriented QA professional with a strong sense of ownership over project quality.
•
Fast learner adept at rapidly understanding complex project domain requirements and adapting to new technologies.
•
Leveraging AI and LLM tools to optimize test case generation and accelerate data validation processes.
•
Good test case design and test data management.
•
Experience working in an agile team (Scrum or Kanban) alongside developers.
•
An understanding of data quality concepts such as completeness, accuracy, consistency and drift.
•
Strong attention to detail, and the confidence to hold the quality line under delivery pressure.
•
Clear written and spoken communication in English.
Nice to have
Nice to Have
•
Working knowledge of Scrapy and other Python-based scraping frameworks.
•
Experience with test automation frameworks.
•
Interest in data science concepts as they apply to data analysis and validation.
•
Interest in using AI and LLM tools to speed up data validation.
Benefits
As a new Zytan, you will:
Become part of a self-motivated, progressive, multi-cultural team.
Have the freedom and flexibility to work from where you do your best work.
Work with cutting-edge open source technologies and tools.
35 days paid holidays