Sreehari S
About Sreehari S
Sreehari S is a Software Engineer with expertise in automated analytics report generation and data pipeline optimization. He holds a dual degree in Engineering Design from the Indian Institute of Technology, Madras, and has experience in various roles, including data analysis and machine learning research.
Work at Quantitative Brokers
Sreehari S has been employed as a Software Engineer at Quantitative Brokers since 2020. In this role, he has orchestrated the automated generation and delivery of pre-trade and post-trade analytics reports using Apache Airflow. His responsibilities include maintaining and optimizing data pipelines to ensure seamless data flow and integrity, which supports the company's analytical capabilities.
Education and Expertise
Sreehari S studied at the Indian Institute of Technology, Madras, where he earned a Dual Degree in Engineering Design with a focus on Automotive Engineering from 2015 to 2020. This educational background has equipped him with a strong foundation in engineering principles and design methodologies, which he applies in his current software engineering role.
Background in Data Analysis and Machine Learning
Prior to his current position, Sreehari S worked as a Data Analyst Intern at Innohabit Technologies for one month in 2017. He also served as a Machine Learning Researcher at PhotoGAUGE from 2018 to 2019, where he contributed to various projects in machine learning. Additionally, he held the position of Computer Vision Research Intern at PhotoGAUGE for one month in 2018, further enhancing his expertise in data-driven technologies.
Internship Experience
Sreehari S gained valuable experience through multiple internships. He interned at Traco Cable Company Limited, a Kerala Government Company, for one month in 2017. His internship experiences have provided him with practical skills in data analysis and software development, which he has leveraged in his subsequent roles.
Technical Contributions
During his career, Sreehari S has developed a centralized reporting framework using Python and Flask, which has improved the efficiency of report generation and delivery. He has also built real-time and historical data analytics services in KDB+/q, contributing to data-driven decision-making processes within the organizations he has worked for.