Narsimha Reddy Ande
About Narsimha Reddy Ande
Narsimha Reddy Ande is a Data Engineer with extensive experience in big data and data solutions. He has worked at Tata Consultancy Services and currently holds a position at Advance Auto Parts, specializing in AWS, Snowflake, and Spark.
Work at Advance Auto Parts
Currently, Narsimha Reddy Ande serves as a Data Engineer at Advance Auto Parts, a position he has held since 2021. His role involves implementing data solutions and managing data processes to support the company's operations. He works in Hyderabad, Telangana, India, contributing to the organization for over three years.
Previous Experience at Tata Consultancy Services
Narsimha Reddy Ande has a background in various roles at Tata Consultancy Services (TCS). He worked as a Big Data Developer from 2020 to 2021 for one year, and prior to that, he served as a Virtual Reality Developer for eight months in 2019 to 2020. Additionally, he was employed as a Python Developer for nine months from 2018 to 2019. His experiences at TCS provided him with a solid foundation in data engineering and software development.
Education and Expertise
Narsimha Reddy Ande holds a Bachelor of Technology (BTech) in Computer Science from St. Peter's Engineering College, where he studied from 2012 to 2016. He furthered his education by obtaining a Master of Science (MS) in Information Technology from Jawaharlal Nehru Technological University, completing his studies from 2016 to 2018. His academic background supports his expertise in data solutions, particularly in AWS Glue, AWS Lambda, and Snowflake.
Technical Skills and Proficiencies
Narsimha Reddy Ande possesses a range of technical skills relevant to data engineering. He has expertise in implementing data solutions using AWS Glue and AWS Lambda, which are essential for cloud-based data processing. He is proficient in managing data storage and retrieval with Amazon S3 and has experience utilizing Snowflake for data warehousing. Additionally, he is skilled in using Spark for big data processing tasks, enabling efficient data handling and analysis.