About

Rajat Venkatesh is a seasoned Big Data professional with over 17 years of relevant experience in the field. He is currently employed as a Senior Staff Software Engineer at LinkedIn, where he is responsible for Big Data Infrastructure Observability. Rajat has a strong background in Datawarehouse, Big Data, and Cloud technologies such as AWS and GCP. He has played a crucial role in conceiving and starting an organization-wide initiative at LinkedIn to collect and organize all events across all components, including Apache Spark, Presto/Trino, Apache Yarn, and HDFS, in an operational data warehouse. This initiative has helped reduce MTTR of AI & DS workflows, improve Apache Spark performance, and provide data lineage through Datahub. Prior to his current role, Rajat worked as a Database Specialist at freelance, where he worked with startups on scaling databases and data warehouses. He has also worked as the Sr. Director of Engineering at Qubole, where he oversaw growth in Presto usage by 6X, Hive usage by 2X, and grew the team by 3X. At Qubole, he set strategy and created differentiation through Qubole Quantum, Rubix, Indexing/Materialized Views, Insights and Recommendations, and transitioned to new architectures like Hive HS2 and Apache Tez. He also founded the Data Engineering team at Qubole. Rajat holds a degree in B.E. from B. M. S. College of Engineering and has completed his education from Carnegie Mellon University. He has a strong technical background in Senior Software Engineering, Big Data, Software Engineering, Data Warehouse, Spark, AWS, infra, HDFS, AI, GCP, ETL, Apache Hive, and Data Engineering. Overall, Rajat is a highly skilled Big Data professional with a proven track record of success in the field. He has a passion for innovation and is constantly looking for ways to improve processes and drive business growth.