Manual Testing Engineer | YASH Technologies Pvt. Limited | Bengaluru, India

Candidate should have a Bachelor’s/ Master’s degree in Computer Science/ IT/ Engineering or Equivalent with 5 to 8 years of hands-on experience in manual software testing or quality assurance. Must have excellent communication & analytical skills.

Key Responsibilities

  • Understanding of product development lifecycles, design change control, document change control, process verification and validation methodologies, manufacturing/production process control methodologies, and servicing.
  • Collaborate closely with hardware and firmware engineers to define and execute test strategies.
  • Participate in Design Verification and Validation (DV&V) testing activities.
  • Experience working with electronic test equipment.
  • Perform Design FMEA with guidance from hardware/software design engineers and principal architects.
  • Report and track defects through the test management system.
  • Analyze, troubleshoot, and identify root causes of product issues.
  • Effectively communicate project updates and technical information to cross-functional teams.

Kindly share your updated resume at anchal.kumari@yash.com with below mentioned details:

Name
Mobile
Key Skills
Total Experience
SAP Experience
Current Company
Current CTC
Expected CTC
Current Location
Notice Period

Company Profile

YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation. At YASH, were a cluster of the brightest stars working with cutting-edge technologies. Our purpose is anchored in a single truth bringing real positive changes in an increasingly virtual world and it drives us beyond generational gaps and disruptions of the future.

At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale.

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