About

Jeevan Joseph is a highly skilled Data Engineering leader with over 12 years of experience in Mapreduce and Spark(Python). He is currently working as a Manager of Data Engineering at Amazon where he has built a team of wonderful human beings who are passionate about their Data Engineering work. Jeevan owns and maintains multiple Redshift clusters running over 500k queries per month dealing with ~20 PB data. He supports an organization of ~7k active data users and guides them in optimizing their queries in Redshift/SQL and Elastic infrastructure. He also leads the team responsible for publishing multiple standardized datasets. Jeevan's expertise lies in EMR-Lambda-DynamoDB-Redshift. He is proficient in data processing using pyspark on transient emr clusters and data being loaded into Redshift. He is working on building a real-time data pipeline to analyze customer's search behavior and purchase probability. He has been the project lead for the central event data analytic pipeline in the company, where he used MapReduce to run batch jobs that process millions of user visits in minutes. Most recently, Jeevan built the Site Optimization and Testing data analysis framework to understand the impact of experiments and user engagements. He creates and maintains multiple Hive tables for teams across the organization (MapReduce, Hive). Jeevan has a Master's degree in Computer Science from the University of Illinois at Chicago and a Bachelor's degree in Electronics and Communication from Mahatma Gandhi University. He has worked as a Software Development Engineer-Intern at Amazon Web Services and as a Member at 1.0 Ventures. Jeevan's technical skills include Data Engineering, MapReduce, SQL, Spark, Python, test, Search, Apache Hive, infra, and Snowflake. He has 11.78 years of relevant experience in the field.