About

Shiva Garg is a highly skilled Lead Big Data and Cloud engineer with over 10 years of experience in the field. He is a certified data engineer who specializes in building data-intensive applications and solving complex architectural and scalability problems. Shiva is well-versed in a range of Big Data technologies, including Hadoop Ecosystem, Apache Spark, Scala, HBase, Phoenix, Hive, Kafka, Google Cloud, MongoDB, and ELK. Throughout his career, Shiva has gained valuable experience in both services and product development. He has worked on numerous projects that encompass the full software development lifecycle, from design and development to testing and deployment. Shiva is currently working as a Lead Big Data Engineer (Vice President) at Citi. Shiva's experience includes working with some of the leading companies in the industry, including Amazon and Publicis Sapient. At Amazon, he was a Data Engineer II and was responsible for designing and developing a Lakehouse (DataLake) using AWS and open-source Hadoop ecosystem technologies. He also built data pipelines to ingest, transform, and store data into DataLake from various operational sources. At Publicis Sapient, Shiva worked as a Senior Associate Data Engineering L2 and was responsible for building large-scale ETL pipelines using Big Data and cloud technologies. Shiva holds a Bachelor of Engineering degree in Computer Science from Chitkara University. He is also an active contributor to the tech community and shares his perspectives on GitHub and Medium. Shiva's technical expertise includes Big Data, Data Engineering, Spark, AWS, Kafka, Scala, Hadoop, Apache Hive, MongoDB, Software Engineering, Amazon Athena, HDFS, and ETL. He is always looking for new challenges and is passionate about building an auto-remediation system. Shiva is an excellent communicator and enjoys discussing code, Big Data, and Cloud computing. With over 10 years of relevant experience, Shiva is a valuable asset to any organization looking to leverage Big Data and Cloud technologies.