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Posted 26 May, 2026

Lead Test Automation Engineer - Merch & Lgx

Photon
India Full Time
Reference: 218_550080_25449

Greetings Everyone



Who are we?

For the past 20 years, we have powered many Digital Experiences for the Fortune 500. Since 1999, we have grown from a few people to more than 4000 team members across the globe that are engaged in various Digital Modernization. For a brief 1 minute video about us, you can check https://youtu.be/uJWBWQZEA6o.


What will you do? What are we looking for?

Overview of the Role

The QE - Sr. QA Engineer will play a critical role in ensuring the overall quality, stability, and reliability of Williams-Sonoma's digital commerce platforms. This role is responsible for driving quality assurance strategies, leading testing efforts across releases, and partnering closely with business, product, and engineering teams to deliver high-quality customer experiences.

Responsibilities include:

Ensure overall quality of deliverables and provide formal test sign-off for releases.
Own and execute testing for production releases in collaboration with business teams.
Lead website testing efforts and ensure readiness for launch.
Provide leadership and technical expertise in Test Automation and Quality Assurance practices.
Monitor QA activities, test results, leaked defects, and conduct root cause analysis.
Identify areas of improvement and implement process enhancements to improve quality outcomes.
Act as an escalation point for all matters related to testing and quality assurance.

Qualifications:

7-9 years of experience in Quality Engineering or Software Testing roles.
Strong experience in front-end QA for e-commerce websites.
Well-versed with Agile methodologies and QA processes.
Thorough understanding of the e-commerce domain.
Hands-on experience in preparing test scenarios and test cases.
Ability to identify gaps in existing processes and recommend continuous improvements.
Excellent written and verbal communication skills.
Strong business domain knowledge relevant to past project experience.
Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or equivalent practical experience.

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