About

Ramanshu Dixit is a highly proficient Senior Data Engineer at KNOLSKAPE with a passion for learning new technologies related to data engineering. With over six years of relevant experience, Ramanshu has developed expertise in SQL, Python, and Spark, with hands-on experience in Serverless Framework, Confluent Kafka, Apache Airflow, and AWS services like EMR, S3, SNS, SQS, and Lambda. Ramanshu has written many spark streaming applications to transform and load data directly from various sources such as AWS Kinesis streams or Apache Kafka. He has also written and scheduled Airflow DAGs to create transient EMR clusters to run spark applications. Ramanshu is comfortable with Hadoop Architecture and has hands-on experience in AWS for big data. Prior to his current role at KNOLSKAPE, Ramanshu worked as a Data Engineer at Ithos Global, where he was responsible for ETL, database management, data wrangling, and business intelligence. He reduced client implementation time from three months to three weeks by extracting data from unstructured and variable documents using text analytics. Ramanshu also worked on using machine learning algorithms to reduce implementation time to a week. Ramanshu has also worked as Deputy Manager at Eicher, where he developed a predictive modeling tool for predicting product launches by the competition in R. He created profitability thumb rules using sensitivity analysis and optimization techniques in MS Excel and analyzed market trends and competition moves to find different patterns for planning strategies based on data-driven decisions. Ramanshu planned Customer Centric Panels to know their present pain and future needs and built dashboards and reports for data visualization on Tableau to make data more insightful. Ramanshu holds a Master of Science degree in Business Analytics from Rensselaer Polytechnic Institute, a Bachelor of Engineering degree in Mechanical Engineering from SGSITS, and a High School degree in Mathematics from Advanced Academy. His tech stack includes Data Engineering, AWS, Python, Spark, SQL, Apache Airflow, Kafka, Big Data, Hadoop, test, product manager, ML, MySQL, and ETL.