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QA Engineer - Data Validation, Test Automation

QA Engineer - Data Validation, Test Automation

Nielsen Media

2 - 6 years

7 - 14 Lacs

gurugram bengaluru mumbai (all areas)

Posted:2 months ago| Platform:

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Skills Required

pytest selenium python

Work Mode

Work from Office

Job Type

Full Time

Job Description

We're looking for a detail-oriented and data-savvy QA Engineer to join our team. You'll play a key role in validating software changes against ground truth datasets, designing automated test pipelines, and ensuring the accuracy and integrity of our product releases. You'll work closely with engineers, data scientists, and product managers to analyze results, catch regressions early, and build confidence in each software release through both automated and exploratory testing.

Responsibilities

Design and execute test plans for software releases with a focus on data accuracy and result validation
Build or extend automated test frameworks to evaluate outputs against ground truth datasets
Create tools and scripts to compare software versions, identify differences, and highlight regressions or improvements
Collaborate with developers to define acceptance criteria, metrics, and success thresholds
Use visualization tools or dashboards to summarize test results for non-technical stakeholders
Investigate failed test cases, analyze logs and data patterns, and suggest areas for improvement
Monitor data drift, outliers, and unexpected behaviors in outputs over time
Contribute to CI/CD pipelines for automated regression testing

Requirements:

2+ years experience in QA Engineering, Software Testing, or similar roles
Strong Python skills (or similar scripting languages)
Familiarity with automated testing frameworks like PyTest, Selenium, or similar
Experience working with structured datasets, CSV/JSON files, and data validation
Knowledge of version control systems (Git), and CI/CD workflows (GitHub Actions, Jenkins, etc.)
Understanding of metrics evaluation (precision, recall, accuracy, etc.) is a plus
Comfortable working in cross-functional teams (engineering, data science, product)

Bonus Skills:

Experience with Pandas, NumPy, or other data analysis libraries
Familiarity with tools like Weights & Biases, Evidently AI, or custom metric dashboards
Exposure to machine learning pipelines or evaluating model outputs
Previous experience with Dockerized environments

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QA Engineer - Data Validation, Test Automation