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Quality Assurance Developer - Dev QA
Job in
Cupertino, Santa Clara County, California, 95014, USA
Listed on 2025-12-15
Listing for:
Intelliswift - An LTTS Company
Full Time
position Listed on 2025-12-15
Job specializations:
-
IT/Tech
IT QA Tester / Automation, Data Analyst, Data Engineer
Job Description & How to Apply Below
Responsibilities
- Compare 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.
- Create 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.
- Document 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.
- Work cross‑functionally with Development, Product Engineering teams.
- Drive QA standards, best practices, and improvements to validation processes.
Skills & Qualifications Technical Skills
- Strong proficiency in Python (Pandas, JSON parsing, data transformation).
- 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, Win Merge).
- Solid understanding of QA methodologies, functional testing, and defect lifecycle.
- Ability 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.
- Experience 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).
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
- 3–7 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.
- Mid‑Senior level
- Contract
- Information Technology
- Software Development
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