Bhupal Geddam
About Bhupal Geddam
Bhupal Geddam serves as the Global Head of Data Platforms at RingCentral, where he focuses on data strategy, architecture, and operations. He has extensive experience in Big Data technologies and has held leadership roles at several prominent companies, including 2K, Workday, and Albertsons.
Work at RingCentral
Bhupal Geddam serves as the Global Head of Data Platforms at RingCentral, a role he has held since 2022. In this position, he is responsible for data strategy, architecture, and operations. His work focuses on leveraging data to enhance business processes and drive decision-making. He operates from the company's Belmont, California location and is involved in various initiatives aimed at optimizing data management and analytics.
Education and Expertise
Bhupal Geddam holds a Master's degree in Engineering from the Indian Institute of Technology, Delhi, and a Bachelor of Technology (BTech) from the National Institute of Technology Warangal. His educational background provides a strong foundation for his expertise in data platforms, big data technologies, and advanced analytics. He possesses extensive knowledge in building reference architecture and conducting RFPs and Proof-of-Concepts for technology selection.
Background
Bhupal Geddam has a diverse professional background in data engineering and analytics. He began his career at Tata Consultancy Services as a Technical Lead from 1999 to 2004. He then worked at Albertsons Companies as a Senior Engineering Manager from 2010 to 2018 and later at Workday as Director of Data Services from 2020 to 2022. Prior to his current role, he was the Director of Data Engineering at 2K for one year in 2019-2020.
Achievements
Throughout his career, Bhupal Geddam has led the development of scalable analytical platforms at major companies, including Cisco, Albertsons, and Workday. He has hands-on experience with various big data technologies such as Hadoop, Spark streaming, and Snowflake. His work has involved designing and developing highly scalable data pipelines using open-source technologies and Massively Parallel Processing (MPP) platforms for efficient data storage and processing.