
Quality Assurance Engineer
2 weeks ago
Location: [Remote]
Job Type: [Full-time]
Experience: 5+ Years
Job Summary:
We are seeking a highly skilled and detail-oriented QA Engineer with hands-on experience in Google Retail Search (GRS) and strong proficiency in SQL. The ideal candidate will be responsible for ensuring the quality and performance of retail search integrations, validating data pipelines, and executing end-to-end testing to ensure an exceptional customer experience in e-commerce search environments.
Key Responsibilities:
- Design, develop, and execute test cases for Google Retail Search implementations.
- Validate search relevance, ranking, and results quality across e-commerce platforms.
- Perform end-to-end testing on data pipelines and integrations between GRS, BigQuery, and associated databases.
- Write complex SQL queries to validate datasets, perform data profiling, and verify ETL jobs.
- Collaborate with development, product, and data engineering teams to identify and resolve issues.
- Monitor test coverage, perform regression testing, and maintain test documentation.
- Automate test scenarios wherever feasible using appropriate QA tools and frameworks.
- Participate in Agile/Scrum ceremonies and contribute to sprint planning, reviews, and retrospectives.
Required Qualifications:
- 5+ years of experience in QA or software testing roles.
- Hands-on experience with Google Retail Search or similar retail search/AI-based search solutions.
- Strong proficiency in SQL, including ability to write complex joins and data validation queries.
- Experience testing e-commerce search functionality, including relevance tuning, search metrics, and user behavior.
- Familiarity with Google Cloud Platform (GCP) and tools such as BigQuery, Cloud Storage, and Pub/Sub.
- Knowledge of QA methodologies, test plans, and defect management tools (e.g., Jira, TestRail).
- Strong analytical and problem-solving skills.
- Excellent communication skills and attention to detail.
Preferred Qualifications:
- Experience with search analytics tools like Google Analytics, Algolia, or Elasticsearch.
- Knowledge of test automation frameworks (e.g., Selenium, Playwright, Cypress).
- Background in retail/e-commerce or working with product catalogs.
- Understanding of machine learning-driven search and personalization.
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