About

Urvarshi Pandey is an enthusiastic and experienced AWS certified Solutions Architect with a deep understanding of AWS Cloud, Apache Spark, Hadoop framework, and their underlying components. With over 10 years of total experience, she has specialized in Big Data/Data Engineering for more than 8 years. She has expertise in building data pipelines for both On-Premise as well as Cloud platforms majorly for data ingestion, migration, transformation, and storage. Urvarshi has hands-on experience in various AWS cloud services including Glue, Glue Catalog, Glue Crawler, Lambda Trigger, S3, Event Notification, S3FS, Athena, RDS, EMR, and On-Premise Hadoop services including HDFS, Yarn, Hive, Impala, Kudu, and Sqoop. She has also worked on various file formats like Parquet, ORC, Sequential, Avro, and JSON. She has a good understanding of scheduling tools such as Control M, AutoSys, Airflow, and Oozie. Urvarshi is proficient in Unix Shell Scripting, Python Programming, PySpark Data-frames, and PySpark SQL. She has excellent problem-solving and troubleshooting capabilities and is highly motivated and result-oriented. She has extensively followed Agile methodology and is familiar with all aspects of Software Development Life Cycle (SDLC). Currently working as a Big Data Engineer at Epam Systems, Urvarshi has previously worked as a Technical Lead at Data Axle and a Big Data Engineer/Analyst at Credit Suisse. She holds a Bachelor of Engineering degree in Electrical, Electronics, and Communications Engineering from Rajiv Gandhi Prodyogiki Vishwavidyalaya. Urvarshi's tech stack includes Data Engineering, Big Data, AWS, Senior Software Engineer, Hadoop, Python, SQL, HDFS, Spark, Apache Airflow, Amazon Athena, ETL, Apache Hive, and Software Engineer. With 10.19 years of relevant experience, Urvarshi is a highly skilled and capable professional in the field of Big Data and Data Engineering.