Godfrey Ndu
About Godfrey Ndu
Godfrey Ndu is a Data Engineer with expertise in parallel programming, data structures, and cloud computing. He has worked at Capital One since 2022 and previously held positions at Intelsat and Stanley Black & Decker, while also studying Electrical and Computer Engineering at Morgan State University.
Work at Capital One
Godfrey Ndu has been employed at Capital One as a Data Engineer since 2022. In this role, he focuses on leveraging his expertise in data engineering to enhance data analytics and visualization processes. He utilizes cloud computing platforms, particularly AWS, to execute various data engineering tasks effectively.
Previous Experience at Intelsat
Prior to his current position, Godfrey Ndu worked at Intelsat as a Data Engineer from 2020 to 2022. During his tenure, he applied parallel programming techniques to improve data analytics and visualization, contributing to the optimization of data processes through a deep understanding of data structures and algorithms.
Internship at Stanley Black & Decker, Inc.
In 2019, Godfrey Ndu completed a three-month internship as a Data Science Intern at Stanley Black & Decker, Inc. in Towson, Maryland. This experience provided him with practical exposure to data science methodologies and enhanced his skills in data analysis and engineering.
Education and Expertise
Godfrey Ndu earned a Bachelor of Science degree in Electrical and Computer Engineering from Morgan State University, completing his studies from 2015 to 2020. His academic background has equipped him with a solid foundation in data engineering, automation, and modeling, which he applies in his professional roles.
Skills in Data Engineering
Godfrey Ndu possesses a range of skills pertinent to data engineering. He is proficient in utilizing Apache Kafka for big data technologies and has experience developing data pipelines and frameworks that enhance performance and efficiency. Additionally, he is skilled in using visualization tools such as Grafana, AWS Quicksight, and Tableau for effective data presentation.