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Logeshwaran n

Logeshwaran n

Dynamic Software Engineer with 2.8 years of experience spearheading client-facing Python development projects. Skilled in requirements analysis, research, and delivering timely solutions. Completed collaborative projects and 3+ independent sub-projects with a 4.3/5 satisfaction score. Seeking a challenging role to leverage expertise in software development and contribute to a forward-thinking organization's success.
  • Role

    Systems Engineer

  • Years of Experience

    4.4 years

Skillsets

  • AWS - 1 Years
  • UNIX - 3 Years

Professional Summary

4.4Years
  • Jan, 2021 - Present4 yr 5 months

    Systems Engineer

    Tata Consultancy Services

Applications & Tools Known

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    Git

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    Perforce

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    MySQL

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    Jenkins

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    Docker

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    Kubernetes

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    UNIX

Work History

4.4Years

Systems Engineer

Tata Consultancy Services
Jan, 2021 - Present4 yr 5 months
    Successfully completed several independent sub-projects, showcasing innovation and technical prowess: Leveraged usage data collected by implementing code usage tracker to identify and eliminate 100% of unused legacy code, resulting in a significant improvement in code quality and system performance. This initiative led to a 37% reduction in codebase size and a 40% decrease in maintenance time, leading to enhanced overall efficiency and stability. Achieved a 60% reduction in code-related issues by implementing the Python import cycle detection tool, elevating code quality and ensuring stability. Fixed more than 80 bugs in a existing Python code base. Successfully implemented a long-pending functionality in the Perl codebase that had been delayed for nearly three years due to its complexity. Developed, tested, and maintained the feature independently for a year as a solo developer, demonstrating strong problem-solving skills and the ability to navigate intricate technical challenges. Functioned as a Platform Automation Engineer, where I successfully transitioned six manual testing processes to automated workflows using Python. This not only enhanced efficiency but also contributed to the overall improvement of the testing infrastructure. Converted legacy test methods to modern ones, resulting in a significant 30-minute reduction in test execution time. This optimization contributed to a more efficient testing process, improving overall productivity.