Vamshi N
About Vamshi N
Vamshi N is a Senior PySpark ETL Developer with over 7 years of experience in data engineering. He has worked for notable companies including Verizon, AbbVie, Fidelity Investments, and Capgemini, and holds a Master's degree in Computer Science from the University of Central Missouri.
Work at Next Pathway Inc.
Currently, Vamshi N serves as a Senior PySpark ETL Developer at Next Pathway Inc. since 2022. In this role, he focuses on developing and implementing ETL processes using PySpark, contributing to the company's data engineering initiatives. His responsibilities include designing data pipelines that enhance data accessibility and usability for analytics.
Previous Experience at Verizon
Vamshi N worked at Verizon as a Senior Data Engineer from 2021 to 2022 in Cary, North Carolina. During his tenure, he was involved in various data engineering projects that supported the company's data management and analytics efforts. His experience at Verizon added to his extensive background in data engineering.
Experience at Fidelity Investments
From 2018 to 2020, Vamshi N held the position of Senior Data Engineer at Fidelity Investments in Morrisville, North Carolina. His role involved developing data solutions that supported financial analytics and reporting. This experience further solidified his expertise in data engineering.
Educational Background in Computer Science
Vamshi N earned a Master's degree in Computer Science from the University of Central Missouri. This academic background provided him with a strong foundation in software development and data engineering principles, which he has applied throughout his career.
Data Engineering Skills and Methodologies
Vamshi N has over 7 years of experience in data pipeline design, development, and implementation. He is skilled in data modeling and has extensive experience with both Waterfall and Agile methodologies within the Software Development Life Cycle (SDLC). His technical skills include writing scripts using Python API, PySpark API, and Spark API for data analysis.