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Quality Assurance Developer - Dev QA

Job in Cupertino, Santa Clara County, California, 95014, USA
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.
Quality Assurance
  • 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.
Documentation & Reporting
  • 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.
Required

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.
Analytical Skills
  • 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.
Bonus Skills
  • 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).
Education & Experience
  • 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.
Seniority level
  • Mid‑Senior level
Employment type
  • Contract
Job function
  • Information Technology
Industries
  • Software Development
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