Job description

About the Role

We are looking for a detail-oriented QA Engineer to join our R&D Department. The candidate will be responsible for validating web-scraped data, reviewing sample files, testing API responses, verifying client-specific requirements, and ensuring that all deliverables meet defined quality standards before submission.

The candidate will work closely with developers, Team Leads (TLs), and Assistant Team Leads (ATLs) to identify defects, maintain quality benchmarks, and prevent recurring data extraction issues.

Key Responsibilities

1. Data Quality Assurance

- Validate scraped data against the source website and client requirements.
- Verify field-level accuracy, completeness, consistency, and data types.
- Identify missing fields, incorrect values, duplicate records, and formatting issues.
- Validate product details, pricing, availability, URLs, identifiers, and other relevant attributes.

2. Sample and Deliverable Validation

- Review sample files before they are marked as QA-passed or submitted to clients.
- Ensure that the output structure, column names, file naming conventions, and data formats match the specified requirements.
- Validate samples against the approved requirements and reference examples.
- Maintain evidence of validation and document any defects identified.

3. API Testing

- Validate API requests and responses, including HTTP status codes, response structures, required fields, and error handling.
- Verify JSON, CSV, Excel, and other required output formats.
- Test pagination, filtering, and relevant request parameters wherever applicable.
- Use Postman or similar tools for API validation.

4. Defect Management and RCA

- Report defects with clear descriptions, sample records, screenshots, and reproduction steps.
- Coordinate with developers and TLs/ATLs for defect resolution and retesting.
- Identify recurring quality issues and contribute to Root Cause Analysis (RCA).
- Maintain defect logs and track issues until closure.

5. Quality Process Improvement

- Develop and maintain QA checklists for different projects and platforms.
- Identify opportunities to automate repetitive validation tasks using Python.
- Track quality metrics, including defect rates, first-pass acceptance, rework, and sample rejection trends.
- Recommend improvements to reduce recurring errors and improve delivery reliability.

Required Skills

- Strong analytical and problem-solving skills.
- Experience in manual testing, data validation, or software QA.
- Basic to intermediate Python knowledge for data validation and automation.
- Experience working with JSON, CSV, Excel, and structured datasets.
- Understanding of REST APIs, HTTP methods, status codes, and response validation.
- Familiarity with Postman, Excel, and basic SQL/MongoDB queries.
- Excellent attention to detail and documentation skills.

Preferred Qualifications

- Experience in web scraping, crawling, e-commerce data, or data extraction projects.
- Knowledge of HTML, CSS selectors, XPath, and browser developer tools.
- Experience with automated testing frameworks or data comparison scripts.
- Familiarity with Git and issue-tracking systems.

Key Performance Indicators (KPIs)

- Accuracy and completeness of QA validation.
- Number of defects identified before client submission.
- Reduction in recurring defects and sample rejections.
- Compliance with project-specific QA checklists.
- Timely completion of QA reviews.
- Quality and completeness of defect reports and RCAs.
- Effectiveness of retesting and defect closure.

Expected Outcome

The QA Engineer will establish an independent quality checkpoint within the R&D workflow, ensuring that samples and deliverables are validated against client requirements before final approval and reducing avoidable rework and quality escalations.

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