Akhil Chalamalasetty
About Akhil Chalamalasetty
Akhil Chalamalasetty is an Associate Director recognized for his expertise in Big Data and AWS Analytics, specializing in the design and optimization of Big Data platforms. He has extensive experience in cloud cost optimization and has worked at FINRA and Cloudwick Technologies, among other companies.
Current Role at FINRA
Akhil Chalamalasetty serves as an Associate Director at FINRA, a position he has held since 2021. His work is based in Rockville, Maryland, where he focuses on Big Data and AWS Analytics. In this role, he is recognized for his expertise in designing and optimizing Big Data platforms capable of managing petabytes of data. His contributions are significant in enhancing the efficiency and effectiveness of data handling within the organization.
Previous Experience at FINRA
Before his current role, Akhil worked at FINRA as a Senior Big Data Engineer from 2015 to 2021. During his six years in this position, he was involved in various projects that leveraged Big Data technologies to support the organization's mission. His experience at FINRA laid the foundation for his current responsibilities and expertise in the field.
Career Background
Akhil Chalamalasetty has a diverse career background in Big Data and analytics. Prior to his tenure at FINRA, he worked at Cloudwick Technologies as a Big Data Engineer from 2014 to 2021. He also held a position as a Hadoop Engineer at NRG Energy for six months in 2014. His early career included a role as a Software Engineer at Zenoti in 2011. This varied experience has contributed to his comprehensive understanding of Big Data technologies.
Education and Expertise
Akhil holds a Master's degree in Computer Science with a focus on Database Administration and Informatics from the University of North Texas. He also earned a Bachelor's degree in Computer Science from Vidya Jyothi Institute of Technology. His academic background supports his expertise in cloud cost optimization and Big Data analytics, enabling him to deliver significant savings in infrastructure and processing costs.