About

Hasil Sharma is an experienced software developer with over 4 years of experience in building scalable machine learning platforms. He is currently working as a Software Engineer at Stripe, where he is part of the Data Streaming Platform team. Hasil is skilled in prominent big data technologies such as Spark, Storm, Kafka, and Cassandra, and proficient in Python, Java, Scala, and C/C++. Hasil completed his Masters in Computer Science with specialization in Data Science Engineering from the University of Colorado Boulder in May 2019. During his academic tenure, he worked on several projects that involved big data processing and machine learning algorithms. Previously, Hasil worked as a Software Engineer II at Microsoft, where he designed and implemented a big data pipeline to allow hundreds of terabytes of data to flow from Office 365 to Dynamics 365 Azure Data Lake on schedule. He used Azure Data Factory for data workflow management with Apache Spark for data processing. Hasil also designed and wrote Apache Spark scripts for multiple data transformations and enhanced the overall cluster usage by scheduling individual transformations, caching, etc. He also worked on creating monitoring dashboards, automated incident creation system in case of failures, build & release pipelines for deployment of data pipeline & web service to different geographical locations. Hasil also worked as a Software Engineer at Microsoft, where he worked to allow data flow from Office 365 Cloud to Dynamics 365 Cloud. He designed scheduled, resilient, and fault-tolerant big data pipelines for data movement. Hasil's education history includes a Masters degree in Computer Science from the University of Colorado Boulder and a Bachelor of Engineering (BE) from Birla Institute of Technology and Science. Hasil's technical skills include Software Engineering, Spark, Azure, Big Data, Web, Python, ML, Data Scientist, Cassandra, Kafka, Scala, Java, and C. He has over 6 years of relevant experience in the field of software engineering and big data processing.