QA Engineer with 4+ years in Mobile & Wearable Testing
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Quality assurance software tester with 4+ years of IT experience in manual and automation testing across mobile and wearable applications. Experienced in STLC, SDLC, accessibility testing, mobile automation, API testing, and CI/CD pipelines. Strong expertise in Google Fitbit and Google Pixel Watch testing, including Appium automation, Postman API validation, Charles Proxy network monitoring, and ADB command-line debugging.
JNTU Anantapur
Bachelor of Technology · Electrical and Electronics Engineering
June 14, 2017 – July 18, 2021
HCL Technologies
Software Engineer
February 16, 2022 – May 28, 2026
Bengaluru, Karnataka, India
Fitbit Wearables (Google Pixel Watch)
April 1, 2023 – May 1, 2026
Worked on Google Fitbit wearable devices and Google Pixel Watch applications, ensuring high quality user experience through manual and automation testing. Performed end-to-end testing of Fitbit wearable applications and Google Pixel Watch features. Developed and executed mobile automation scripts using Appium framework for wearable device validation. Executed API testing and validation using Postman for backend and health data integration services. Used Charles Proxy for network traffic monitoring, request/response validation, and debugging API failures. Worked extensively with ADB commands for log capturing, device debugging, APK installation, and test execution. Conducted accessibility testing using Android Talk Back and iOS Voice Over for smartwatch applications. Executed regression, functional, smoke, and E2E testing across multiple wearable builds. Analysed logs and performed failure analysis to identify defects and collaborate with developers for resolution. Maintained transparent communication with managers and leads by providing daily status reports and testing updates. Participated in knowledge transfer sessions and supported team members in debugging and issue resolution.
Matter / CHIP Testing (Google Nest Devices)
June 1, 2022 – December 1, 2022
Validated Google Nest device communication with third-party IoT devices using Matter/CHIP protocol. Executed smoke, functional, and regression testing for firmware validation. Tested integrations with ESP32, NRF, and EFR32 third-party devices. Monitored logs, raised bugs in Buganizer, and reduced defect triage time. Prepared and updated test scenarios and test cases. Performed functional, smoke, and regression testing for Google Nest devices and Matter/CHIP integrations. Validated connectivity and communication between Google Nest products and third-party devices such as ESP32, NRF, and EFR32 boards. Executed firmware validation testing for newly released builds and monitored device behaviour. Analysed logs and performed debugging using ADB commands and internal Google tools. Raised and tracked defects using Buganizer with detailed logs and reproduction steps to reduce triage effort. Prepared and maintained test scenarios, test cases, and execution reports. Worked closely with Google leads and cross-functional teams during daily and weekly status calls. Performed end-to-end testing for voice assistant, on/off controls, temperature control, and smart home functionalities. Supported knowledge transfer sessions and assisted team members in issue debugging and resolution.
Cultural Fit Analysis
The candidate's experience with diverse projects like Fitbit Wearables and Matter/CHIP testing for Google Nest devices shows adaptability and a broad skill set relevant to modern tech environments. Their involvement in knowledge transfer and team support indicates a collaborative mindset. The focus on end-to-end testing and user experience aligns well with a quality-driven culture. The candidate's background in Electrical and Electronics Engineering, combined with software testing, suggests a versatile approach to problem-solving, which can be a strong cultural asset.
Soft Skills & Operational Fit
The candidate demonstrates strong collaboration skills through participation in knowledge transfer sessions and supporting team members. Their experience in providing daily status reports indicates good operational communication. The ability to analyze logs and perform failure analysis suggests strong problem-solving and analytical skills, crucial for a senior QA role. The candidate's experience with Google projects implies an ability to work within large, structured organizations.