Tiffany Rabeya
About Tiffany Rabeya
Tiffany Rabeya is a Hadoop Developer with extensive experience in data engineering and software testing. She has worked at notable organizations including the Federal Reserve Bank of New York and Gap, and has developed various data pipelines and implemented partitioning strategies in Hive.
Work at Federal Reserve Bank of New York
Tiffany Rabeya has been employed as a Hadoop Developer at the Federal Reserve Bank of New York since 2019. In this role, she has developed data pipelines using StreamSets Data Collector. These pipelines facilitate the storage of data from Kafka into various systems, including HDFS, Solr, Elastic Search, HBase, and MapR DB. Her work focuses on enhancing data management and processing capabilities within the organization.
Previous Experience as Hadoop Developer at Gap
Prior to her current position, Tiffany worked as a Hadoop Developer at Gap from 2017 to 2018 in San Francisco, California. During her tenure, she contributed to various Hadoop-related projects, enhancing the company's data processing capabilities. Her experience at Gap provided her with valuable insights into the retail sector's data management needs.
Experience as Software Test Engineer at RBC
Tiffany Rabeya served as a Software Test Engineer at RBC from 2015 to 2017 in Jersey City, New Jersey. In this role, she was responsible for testing software applications, ensuring their functionality and reliability. This position allowed her to develop a strong foundation in software testing methodologies and practices.
Education and Expertise
Tiffany completed her Bachelor's degree at Dhaka City College, where she studied from 2010 to 2012. She also attended Ideal School and College from 2001 to 2010 and Richmond Hill High School. Her educational background has equipped her with the necessary skills in data processing and software development, particularly in Hadoop and Spark technologies.
Technical Skills and Projects
Tiffany Rabeya has developed partitioned Hive tables and implemented partitioning and bucketing in Hive. She has created Spark scripts using Python shell commands based on project requirements. Additionally, she has worked on data migration, utilizing MapReduce programs and Spark transformations. Her experience includes exploring Directed Acyclic Graphs (DAGs) and automating processes using AirFlow pipelines.