QA Engineer - Data & Automation

Weekday AI

Full-time

Remote

Worldwide

Description

This role is for one of the Weekday's clients

**Salary range: Rs 700000 - Rs 900000 (ie INR 7-9 LPA)

**Min Experience: 1 years

JobType: full-time

We’re seeking a QA Engineer who’s passionate about blending data, automation, and quality to elevate product reliability. In this role, you’ll be instrumental in driving quality assurance through a combination of automated testing, data analysis, and insightful reporting. From building real-time dashboards to writing scripts that streamline testing, you’ll play a key role in ensuring our platform delivers exceptional user experiences.

Requirements

What You’ll Do:

Create and Maintain QA Dashboards: Build dashboards to track essential QA metrics like test coverage, defect trends, regression issues, and more.
Analyze Test Data: Dive into both manual and automated test results to uncover insights, flag potential issues, and recommend improvements.
Build Data Pipelines: Extract and consolidate data from tools such as Jira, TestRail, Jenkins, and GitHub to enable real-time quality reporting.
Develop Automation Scripts: Write and maintain test scripts using Python, Selenium, Playwright, or similar tools to improve testing efficiency and reliability.
Collaborate Cross-Functionally: Work with QA, Engineering, and Product teams to define and track quality indicators aligned with business goals.
Maintain QA Documentation Integrity: Ensure consistency and accuracy of QA data across systems and tools.
Integrate with CI/CD Pipelines: Support automation integration within continuous integration workflows to provide faster, more reliable feedback.

What You Bring:

2+ years of experience in QA, test automation, or quality-focused data analytics.
Solid understanding of QA fundamentals: test execution, defect lifecycle, and regression testing.
Proficiency in Python for scripting and data handling.
Hands-on experience with test automation frameworks (Selenium, Playwright, Cypress, etc.).
Strong SQL and spreadsheet skills (Excel or Google Sheets).
Familiarity with BI tools like Tableau, Looker, or Power BI for visualizing QA trends.
Exposure to CI/CD tools and concepts (e.g., Jenkins, GitHub Actions).

Key Skills: