Mohammad Miah
About Mohammad Miah
Mohammad Miah is a Hadoop Developer currently employed at UBS in New York since 2019. He has extensive experience in data processing and transformation using Hadoop technologies and has previously worked for companies such as Gap, ViacomCBS, and Blackstone.
Work at UBS
Mohammad Miah has been employed at UBS as a Hadoop Developer since 2019. His role involves working in New York, United States, where he has contributed to various data processing tasks. His responsibilities include importing data from multiple sources into HDFS using Sqoop and applying transformations with Hive and Apache Spark. Miah has been instrumental in developing scalable data solutions and ensuring efficient data management within the organization.
Previous Experience in Hadoop Development
Prior to his current position at UBS, Mohammad Miah worked at several notable companies as a Hadoop Developer. He was employed at Gap from 2016 to 2019, where he continued to enhance his skills in data processing. Miah also worked at ViacomCBS for one year from 2015 to 2016 and at Blackstone for seven months from 2014 to 2015. His experience across these organizations has equipped him with a solid foundation in Hadoop technologies and data management.
Education and Expertise
Mohammad Miah earned his Bachelor's degree in Accounting from York College (CUNY), where he studied from 2001 to 2006. This educational background provides him with a strong analytical foundation that complements his technical skills in Hadoop development. Miah's expertise includes data processing using Spark RDDs and Python (pyspark), as well as developing architecture documents for distributed data solutions.
Technical Skills and Contributions
In his role as a Hadoop Developer, Mohammad Miah has been involved in various technical tasks. He has developed architecture documents and guidelines for scalable distributed data solutions using Hadoop. Additionally, he has configured Splunk alerts to capture log files during execution and store them in S3 buckets, enhancing the monitoring and management of data processes within the Hadoop ecosystem.