About

Rajasekhar Palantla is a Principal Software Engineer at Silicon Valley Bank with over 15 years of experience in Big Data, Analytics, Business Intelligence, and Data Warehousing. He has extensive knowledge and experience in Spark, Scala, Hadoop, and Hive, and has worked on BI/DWH projects related to Mortgage, Warranty, and eCommerce using ETL tools such as Informatica, SQL Server DTS Packages, and Pentaho Kettle. He is also proficient in OLAP Tools such as Pentaho Report Designer, SAS Web Report Studio, and Business Objects. Rajasekhar is well-versed in designing and implementing Data Mart applications, mainly transformation processes using ETL tools like Informatica, Pentaho Kettle, SQL Server Management Studio (SSIS), SAS, R, and Python. He has worked with various databases such as Oracle, MySQL, and SQL Server and has good experience in data visualization tools like Tableau and Qlik. He has a thorough understanding of Data Warehouse concepts like Star Schema, Snowflake, Dimension, and Fact tables and Data Modeling. With excellent analytical and logical skills, Rajasekhar has the ability to provide quality technology solutions within committed time frames. He has worked with companies such as Harman and Dataxu in the past, holding positions such as Associate Director and Principal Data Engineer, respectively. Rajasekhar completed his B.Tech in Electronics and Electrical Communications Engineering from IIT Kharagpur in 2005. Prior to that, he completed his 12th from Gowtham College, Vijayawada, and his 10th from Besant School, Vizianagaram. His tech stack includes Software Engineering, SQL, ETL, AWS, Spark, Data Warehouse, Scala, Designer, Hadoop, Python, MySQL, Web, Senior Software Engineering, Data Engineering, Snowflake, Apache Hive, Kafka, Azure, Backend, Infra, AWS Glue, Apache Airflow, Amazon Athena, QA, Product Designer, ML, Data Scientist, Search, Integration, Mobile, and Frontend. Overall, Rajasekhar has 17.03 years of relevant experience and is a highly skilled software engineer with a strong background in Big Data, Analytics, BI, and DWH.