Quality Assurance Engineer Job Vacancies in Guindy

Role: Quality Assurance Engineer (Data & API)SUMMARYThe Quality Assurance Engineer partners with Engineering, Data, and Developmentteams to ensure client requirements are implemented correctly and reliably acrosshighvolume data pipelines. This role reviews requirements, designs test strategies, andexecutes automated and manual validation-emphasizing shiftleft practices andrepeatable automation. Candidates are former developers or Software DevelopmentEngineer in Test (SDET) who can effectively test large datasets, craft complex SQL fordata comparisons, and collaborate within a single, shared sprint cadence.ESSENTIAL DUTIES AND RESPONSIBILITIES Configure, implement, and maintain automated testing frameworks for data and APIvalidation (DBT tests, Pytest, SQL validators). Translate JIRA user stories and acceptance criteria into comprehensive test plans,scenarios, and data validation scripts. Ensure requirements traceability by mapping test cases and validation scriptsdirectly to client requirements and acceptance criteria, maintaining cleardocumentation throughout the lifecycle. Design and execute unit, integration, smoke, regression, and endtoend tests alignedto the recommended QA & automation framework. Validate large datasets for completeness, accuracy, timeliness, lineage, and schemaconformance, author complex SQL for data comparison. Coordinate with Engineering to enable shiftleft testing - QA participates ingrooming, planning, and daily standups; quality is a shared responsibility. Assist with user acceptance testing (UAT) and production validation, includingpostrelease smoke testing and regression cycles. Analyze test outputs, identify defects, document issues, and drive rootcauseanalysis; champion environment parity (VAL mirrors PROD). Contribute to release governance: freeze windows, QA gates, rollback plans, andrelease logs; ensure test evidence is captured. Continuously improve tools, templates, and processes; propose JIRA automation toautocreate QA stories from engineering stories. Develop domain knowledge of client data products, pipelines, integrations, and KPIs. Maintain comprehensive test documentation, including test cases, scripts, andresults, to support audits and compliance. Conduct performance and security testing as required to ensure robust, scalable,and secure solutions. Advocate for user experience and usability in all testing activities.AGILE & COLLABORATION EXPECTATIONS Active participant in Agile ceremonies (grooming, planning, standups, demos, retros)within a single, shared sprint cadence. Story readiness includes defined test criteria and data availability; QA estimatestracked alongside development. Promote predictable velocity by integrating automated tests into CI; definition ofdone includes -tested and validated.- Stay current with emerging QA tools, technologies, and best practices; proactivelyrecommend improvements to processes and frameworks.REQUIRED QUALIFICATIONS Former software developer or SDET with handson coding experience (Pythonpreferred). Expertise in SQL and relational databases; able to design complex validationqueries for large datasets. Demonstrated experience testing data pipelines, ETL/ELT workflows, and APIs inhighvolume environments. Practical knowledge of Airflow (or similar orchestration), DBT, and CI systems;experience validating DAG executions. Proficiency with automated testing tools (Selenium/Cucumber/Playwright for UIwhere applicable; Pytest for services; DBT for data). Proficiency with version control systems (e.g., Git) and defect tracking tools (e.g.,Jira, Azure DevOps). Experience with JIRA and Agile development methodology; comfortable with sharedsprint delivery. Strong critical thinking; challenges ambiguous requirements and drives clarity inacceptance criteria. Excellent communication skills; able to partner with Product Owners and Engineersto define testable stories.PREFERRED / DOMAIN EXPERIENCE Experience with liveevent data, broadcast schedules, media assets, or fanengagement platforms. Experience with bigdata validation (Snowflake/BigQuery/Redshift) and performancetesting of queries at scale. Familiarity with API contract testing, data lineage tools, and dataset comparisonframeworks. ISTQB or equivalent certification is a plus. Experience with cloud-based data platforms (AWS, Azure, GCP) is a plus.