About

Dinesh Rajput is a highly skilled and experienced BigData Engineer, Team Lead, and Senior Engineer with over 10 years of experience in the field. He is proficient in working with a wide range of technologies, including Hadoop-MapReduce, Pig, Hive, Hbase, Sqoop, Solr, Spark, Storm, Kafka, Cassandra, MongoDB, Redis, Python, R, RHadoop, MLLib, OpenCV, Tesseract, YOLO, and more. He also has hands-on experience with AWS, Linux, EC2, CFT, Elastic Search, IAM roles, Cognito, S3, EMR, Lambda, Redshift, DynamoDB, Managed Kafka, Git, Jenkins, Docker, and Kubernetes. Dinesh has managed Hadoop clusters and has experience connecting Tableau BI, Pentaho, and Superset with Hadoop clusters. He has also developed UI on top of Hadoop clusters and has imported data from SQL Server/Oracle to HIVE and exported it back using Sqoop. He is well-versed in Spark Structured Streaming with Kafka and Oracle with failure management, Spark Job tuning, Join Optimization, Time Calculation, Code Tuning, Debug Process flow, Code Cleanup, and Code Review. Dinesh is a team player with excellent analytical skills to identify key issues and provide solutions. He has a thorough understanding of the SDLC process and has experience in requirement analysis, design, development, testing, UML, OOAD, change request management, and maintenance. He has worked on POCs such as COBOL mainframe data parser, JSON dynamic schema, MongoDB with Spark, HiBench Hadoop benchmark, OLTP with Kudu NoSQL, lambda architecture, Hadoop Spark cluster on Kubernetes and Docker, and Thingsboard IoT customized as per need with MQTT and real-time sensor controller. Dinesh has worked with companies such as Qualys and Innova Solutions as a Lead Data Engineer and Sr. Lead Data Engineer, respectively. He has also worked as a Lead Software Engineer for Clairvoyant, leading a team of six members for the client PayPal. He has a Bachelor of Engineering degree from Acropolis Institute of Technology and Research, Indore, India. Dinesh's TechStack includes AWS, Spark, Hadoop, Data Engineering, Kafka, Java, SQL, GCP, Apache Hive, MongoDB, Redis, ML, NoSQL, Cassandra, MapReduce, Spring, HDFS, Web