About

Vishal Saxena is an accomplished Senior Data Lab Architect with Amazon Web Services (AWS), possessing over 10 years of relevant experience. He is an expert in developing big data solutions using Spark, Hive, HDFS, Scala, YARN, and AWS services such as Glue, Athena, S3, DMS, IAM, EC2, Oracle, SQL Server, and Informatica. He has worked on data lake implementations on AWS for some of the biggest NBFCs and banks in India, creating the overall architecture of data lake on AWS, including the current system analysis, and target system analysis. Vishal has extensive experience in data pipeline creation, consisting of data transformations, sourcing, mapping, conversion, and loading. He is proficient in Spark SQL, data frames and dataset API, as well as RDDs (Resilient distributed datasets), and implementing end-to-end solutions from source to target. He is an expert in designing optimized solutions in Spark using various compression and encoding techniques, bucketing, partitioning, etc. He has hands-on experience working on open file formats such as Parquet, ORC, and Avro, applying various compression techniques such as snappy, LZO, Gzip, and bzip2 to make efficient big data solutions. Vishal has also created budgets and estimations for AWS services and done complete analysis on the sizing of the current system, based on which the overall AWS data lake BOM was created. He has built complex ETL logics using map-side join, bucket map joins, and sort merge bucket joins, etc. He proactively communicates with various stakeholders on closing the business requirements. Before joining Amazon, Vishal worked as a Senior Cloud Engineer with SAS and as a Manager with EY. He holds a B.Tech degree in Information Technology from APJ Abdul Kalam Technological University, Kerala. He completed his 12th from Bishop Conrad School and his 10th from St. Francis Convent School, both in India. Vishal's tech stack includes AWS, Senior Software Engineer, Spark, SQL, HDFS, Amazon Athena, Web, Scala, ETL, and Apache Hive. He is a highly skilled professional with a proven track record of delivering successful big data solutions in various domains on-premises as well as on the cloud.