TARUN SHEDHANI
*********@*****.*** 816-***-**** Kansas City, MO LinkedIn
OBJECTIVE
Seeking a position as an engineering candidate in initiatives that utilize state-of-the-art, software components with a creative, technology- driven organization in an environment that encourages innovative thinking, recognition, and career development. EDUCATION
University of Missouri-Kansas City Kansas City, MO
Master of Science, GPA 3.6/4 (Graduation May 2016) Rajiv Gandhi Technical University India
Bachelor of Engineering, GPA 3.5/4 (June 2011)
SKILLS AND INTERESTS
DISTRIBUTED PROGRAMMING : Web Services (REST)
WEB/CLOUD TECHNOLOGIES : HTML, Javascript, Ionic framework, AWS, Azure, Ajax
DATABASE : MYSQL, Hive, MongoDB
SUBJECTS : Software Architecture and Design, SDLC, Cloud Computing, Hadoop WORK EXPERIENCE
Engineering Intern, Verizon Wireless (Alpharetta, GA) June 2015 – December 2015
Implemented the solution for internal projects.
Learnt software development life cycle approach with agile methodology.
Debugging of code and automated various manual processes using cron jobs and scripts. Technical emphasis: Java, Unix, subversion tools and shell scripting Associate Software Developer, NetCracker (Hyderabad, India) July 2011 – July 2014
Implemented/coded the product solution for various clients.
Supported various testing phases (integration test, system test, parallel test)
Mentored the new hires and conducted knowledge sharing sessions. Technical emphasis: Java, Mediation Zone (in-house tool), agile methodology. ACADEMIC PROJECTS
Title: Health Scope Android App September 2015 – November 2015
This project was an android app capable of calculating blood glucose, hypertension and BMI
Results were displayed using external APIs in intuitive visual manner
The server was created using java annotation classes and was deployed on IBM Bluemix Learning points: Ionic framework for client side, MongoDB for storing the result, D3 APIs for visualization, Java annotative classes Title: Comparing two cloud database (Cloudant DB vs MongoLab) September 2015 – December 2015
This project was designed to compare two cloud database (document driven)
Store and Retrieve technique was used to determine the response time and throughput of the databases
Client Server application was built in order to determine the availability of the databases. Learning Points: Cloud Computing, DBaaS, SaaS, cURL, LoadStorm Title: Twitter Sentiment analysis including facial and recognition using Big Data January 2015 – April 2015
Primarily designed to analyze the raw data and process the data to into graphical representation.
Twitter’s json format was the input to the project and MapReduce framework was used to transform the data.
Sentiment, facial and age analysis using Alchemy API in order to report the demographics of the data set. Learning points: Hadoop, Java, NoSql (Hive), IBM Bluemix, Alchemy API, Ajax, Kanban