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QA Automation Engineer with 4+ years in test automation using JavaScript/TypeScript, Java, TestCafe,
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Proactive Software Test Engineer with 2+ years of experience in JavaScript/TypeScript, Java, TestCafe, Playwright and Selenium WebDriver, improving test efficiency and coverage by automating over 300+ testcases.
Sinhgad Institute of Business Administration and Research
Masters of Computer Application (MCA)
August 1, 2024 – Present
Poona College of Arts, Science and Commerce
Bachelor of Computer Science
August 1, 2022 – June 30, 2022
Katalon Studio
Product Support Engineer (Automation Testing)
October 1, 2025 – Present
India
Salt Technologies
Associate Software Tester
December 1, 2024 – October 1, 2025
Pune, Maharashtra, India
12th Wonder
Associate Software Test Engineer
September 1, 2023 – November 1, 2024
Pune, Maharashtra, India
Technogise Private Limited
Quality Consultant (QA)
August 1, 2022 – March 1, 2023
Pune, Maharashtra, India
Society for Health and Medical Technology (SHMT)
Automation Software Tester
September 1, 2021 – March 1, 2022
India
Cultural Fit Analysis
The candidate's experience across various companies, including product support, software testing, and quality consulting, indicates adaptability to different organizational cultures. Their collaboration with global clients and cross-functional teams suggests a team-oriented mindset. The diversity of tools and technologies used (Playwright, TestCafe, Selenium, Jira, Salesforce, Git) shows a broad skill set and willingness to learn, which aligns well with a culture of continuous improvement.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills, root cause analysis, and effective communication, as evidenced by their roles in product support and collaboration with cross-functional teams. Their experience in managing multiple projects and prioritizing tasks indicates good operational fit for a dynamic QA environment. The use of AI tools for troubleshooting also highlights an adaptive and efficient approach to problem-solving.