Utkarsh Shaw
About Utkarsh Shaw
Utkarsh Shaw is an SDE 1 Backend at Trademo, where he has worked since 2023. He has experience as a Data Engineer Intern and SDE Backend Intern, and he has demonstrated strong technical skills through various projects, including leading the development of the Trade Compliance product and optimizing backend systems.
Current Role at Trademo
Utkarsh Shaw is currently employed at Trademo as an SDE-1 Backend, a position he has held since 2023 in Gurugram, Haryana, India. In this role, he is responsible for various backend development tasks, including leading the development of the Sanctions Screener. His work involves implementing complex search and aggregation queries in Elasticsearch, showcasing his technical expertise in backend systems.
Previous Experience at Trademo
Utkarsh Shaw previously worked at Trademo in two internship roles. He served as a Data Engineer Intern for four months in 2022 and as an SDE Backend Intern for six months in 2023, both in Gurugram, Haryana, India. During his internships, he gained practical experience in backend development and data engineering, contributing to various projects and initiatives.
Mentorship and Team Leadership
During his time at Trademo, Utkarsh mentored a team of six interns in the development of the Trade Compliance product. He provided guidance and support to ensure successful project outcomes, demonstrating his leadership abilities and commitment to fostering a collaborative work environment.
Education and Technical Skills
Utkarsh Shaw studied at Dronacharya College of Engineering, where he earned a Bachelor of Technology (BTech) in Computer Science from 2019 to 2023. His academic background has equipped him with strong technical skills, which he applied in various projects, including independently designing the architecture and handling backend development for the Product Master.
Technical Contributions
Utkarsh has made significant technical contributions during his tenure at Trademo. He developed robust asynchronous tasks and a message queuing system using Celery and RabbitMQ. Additionally, he optimized RAM usage for the Sanctions Screener, enhancing the performance and efficiency of the application.