Akhil Garidepally
About Akhil Garidepally
Akhil Garidepally is a Data Engineer at Rx Savings Solutions in Kansas City, Missouri, with extensive experience in Hadoop ecosystems and Spark applications.
Current Role at Rx Savings Solutions
Akhil Garidepally currently works as a Data Engineer at Rx Savings Solutions in Kansas City, Missouri, United States. He leverages his extensive background in data engineering to develop and maintain data architectures and processing pipelines. This role involves working with a variety of tools and technologies to ensure data is processed efficiently and accurately to serve the organization's needs.
Previous Roles and Experience
Akhil previously worked as a Data Engineer Intern at Rx Savings Solutions in 2022, where he gained practical experience relevant to his career. Prior to that, he served as a Software Engineer at GSPANN Technologies, Inc in Hyderabad, Telangana, India from 2018 to 2021. During his tenure at GSPANN Technologies, he was involved in multiple software engineering projects that further built his skills in data processing and software development.
Education and Expertise
Akhil Garidepally earned his Master's degree in Computer Science from the University of Missouri-Kansas City between 2021 and 2022. His academic and professional experiences have equipped him with expertise in major components of the Hadoop Ecosystem, including Spark, MapReduce, HDFS, YARN, Hive, HBase, Kafka, Sqoop, and Airflow. Additionally, he possesses strong programming skills in Spark, PySpark, and Python.
Technical Skills and Projects
Akhil has developed multiple Kafka Producers and Consumers from scratch based on software requirement specifications. He has hands-on experience with various Hadoop distributions such as Cloudera, Hortonworks, and AWS EMR. His proficiency extends to developing production-ready Spark applications using Spark RDD APIs, DataFrames, and Spark-SQL. He is also knowledgeable in reporting tools like Incorta and Tableau.
Experience with Spark and Data Processing
Akhil Garidepally has substantial experience using Spark for large-scale data processing tasks. His work involves data cleansing, data de-normalizations, and data aggregations. This expertise allows him to efficiently handle and process vast amounts of data, which is critical for supporting data-driven decision-making processes within organizations.