Ankush Sharma
About Ankush Sharma
Ankush Sharma is a Senior Engineering Manager for Core Ingestion at TRM Labs, where he has worked since 2024. He has a strong background in data engineering, having held key positions at companies like Hulu, Amazon, and LegalZoom.
Work at TRM Labs
Ankush Sharma has been serving as the Senior Engineering Manager for Core Ingestion at TRM Labs since 2024. His role is based in Los Angeles, California, and he operates in a remote capacity. In this position, he is responsible for overseeing engineering processes related to data ingestion, leveraging his extensive background in data architecture and engineering.
Previous Experience at Hulu
Prior to his current role, Ankush Sharma worked at Hulu as a Principal Data Architect from 2015 to 2022. During his tenure, he played a key role in designing and implementing data solutions for various aspects of the streaming service, including content management, advertising, and user session analysis. His contributions were significant in enhancing the data infrastructure for Hulu/Disney Streaming Services.
Experience at Amazon
Ankush Sharma held the position of Senior Manager of Data Engineering at Amazon from 2022 to 2024. In this hybrid role based in Santa Monica, California, he managed data engineering projects and teams, focusing on optimizing data processes and improving data accessibility for various applications within the organization.
Educational Background
Ankush Sharma earned a Bachelor of Science with Honors in Computer Science from Delhi University, where he studied from 1997 to 2001. He furthered his education by obtaining a Master of Science in Computer Science from the University of Southern California, completing his studies from 2001 to 2003. Additionally, he completed his High School Equivalence Certificate Program at Air Force Bal Bharti School from 1995 to 1997.
Technical Skills and Achievements
Ankush Sharma possesses extensive experience in optimizing data storage, manipulation, and analysis. He is proficient in using tools such as Spark, Snowflake, Databricks, Looker, and Thoughtspot. Notably, he successfully reduced Snowflake credits usage by transitioning ETL processes to Databricks using Spark, demonstrating his ability to enhance operational efficiency in data management.