Quality Assurance Developer - Dev QA (Cupertino) at Intelliswift - An LTTS Company

Key ResponsibilitiesData Validation & ComparisonCompare Excel output vs JSON output to ensure correctness, completeness, and structural integrity.Validate schema, key-value pairs, formatting, and business rules.Normalize and flatten JSON to align with Excel tabular formats.Write and maintain Python scripts (Pandas/JSON libraries) for automated data comparison.Quality AssuranceCreate detailed test plans, test scenarios, and test cases for data validation workflows.Perform functional testing on services, APIs, and data pipelines that generate outputs.Identify defects, analyze root causes, and work closely with developers to resolve issues.Validate regression outputs to prevent data drift across releases.Documentation & ReportingDocument data comparison rules, testing procedures, and validation logic.Provide clear defect reports with reproducible steps and detailed examples.Create and maintain QA dashboards, logs, and reports as required.Team CollaborationWork cross-functionally with Development, Product Engineering teams.Drive QA standards, best practices, and improvements to validation processes.Required Skills & QualificationsTechnical SkillsStrong proficiency in Python (Pandas, JSON parsing, data transformation).Advanced Excel skills (VLOOKUP/XLOOKUP, pivot tables, conditional formatting).Experience with JSON, nested data structures, and schema validation.Familiarity with API testing using tools like Postman or similar.Experience with data diff tools (VS Code diff, Beyond Compare, WinMerge).Solid understanding of QA methodologies, functional testing, and defect lifecycle.Analytical SkillsAbility to analyze complex datasets and identify inconsistencies.Strong problem-solving skills and ability to debug logical errors.Ability to interpret business rules and apply them to data validation.Bonus SkillsExperience with SQL (joins, filters, data validation).Knowledge of automation frameworks (PyTest, Robot Framework).Experience with Jupyter Notebooks for data visualization.CI/CD pipeline familiarity for automated test execution.Understanding of cloud-based storage (AWS S3, Azure Blob).Education & ExperienceBachelors degree in Computer Science, Information Systems, Engineering, or related field.37 years of experience in QA, Data QA, Data Validation, or Data Engineering QA roles.Experience validating outputs from APIs, ETL pipelines, or reporting systems is highly desirable.