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About me
Graduate student at The University of Texas at Arlington. I am currently pursuing Masters in Computer Science in the Majors Artificial Intelligence and Database Systems . Prior to this,  I have Worked as a Software Engineer for 3 years at Tech Mahindra in the field of Application Support in the production environment. I have completed my under graduation in the field of Computer Science Engineering.
Home: About Me
Professional Experience
Highly self-motivated and goal oriented professional with 3 years of experience as a Software engineer in the Middleware Integration tool like Trusted Link Enterprise, ticketing tool CA-Service Desk and SAP-sales and distribution on Production Support and Implementation. Good Knowledge in Java, Hadoop and its components like HDFS, Map Reduce, PIG, HIVE, SQOOP and OOZIE.
June 2016 - December 2018
Project Description :
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Application Production support that extends to L2 and L3 support in coordination with business units and customer. Primarily this involves handling SAP Idoc errors (Inbound and Outbound), end-to-end file flow of the data from various trading partners for all the applications such as Elemica, World Account, FTS & FSS, EDI-Coatings. Plus On-boarding on new Trading partners in the , Creating and Modifying Maps using the TLE Map Editor.
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Roles and Responsibilities :​
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Handled both SAP Inbound and Outbound Idoc failurs.
Handled different issues that requires knowledge in SAP T-Codes such as VA03, VA02, VF03, VF02, VL03N, VT03N, SE16(EDPAR, LIKP), WE02, WE05, WE09, WE20, YEDI, ME23N, SM37, SA38.
Finding missed Electronic data interchange messages and analyzing the transmission logs ensuring delivery.
Performed EDI Maps testing and validations using test data.
Modified Maps (X12 - 850,855,860,810) using TLE map editor.
Archiving and maintenance of EDI messages and logs daily using UNIX.
Checking the status of Scheduled Jobs in SAP.
Creating the profiles for the trading partners to share files using different server in Client specified dashboard.
Solving Incidents and Change Orders for Europe and North America within the defined SLA criteria.
Creating the firewall request for new partner and setting up the public key.
Hosting Periodic update and enhancement meeting with SME's and team.
November 2015 - May 2016
Completed the Entry Level Integrated Training and Enablement program in Java Stream .
Home: Experience
Academic Qualifications
January 2019Â - May 2021
Masters in CS, The University of Texas at Arlington
Graduate student at The University of Texas at Arlington. I am currently pursuing Masters in Computer Science in the Majors Artificial Intelligence and Database Systems.
August 2011Â - June 2015
Bachelor of Technology
Bachelor of Technology in Computer Science Engineering from Keshav memorial Institute of Technology, JNTU, Hyderabad
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Certifications and Achievements
Completed Entry Level Integrated Training and Enablement program in JAVA Stream in Tech Mahindra Hyderabad conducted during the Period November 2015- April 2016.
Completed Cambridge ESOL Entry Level Certificate in ESOL International (Business English) (Entry 3) on 30/04/2012.
Received two BRAVO awards from the Client in the BASF project in a short span for my sincere efforts and hard work.
Home: Education
Skills
Programming Languages : Java, Core Java, Advanced Java, EDI
Scripting Languages : HTML, CSS, XML, JavaScript, JSP
Big Data Ecosystem : HDFS, MapReduce, PIG, HIVE, SQOOP
Frameworks : Spring, Hibernate, Hadoop
Tools : GXS TLE (Trusted Link Enterprise) V6.2, SAP Net Weaver 740, CA Service Desk Manager, FileZilla, WinScp, PUTTY
Specifications : ANSI X12 EDI, HTTPS, FTP, SFTP Protocols
Databases : Oracle 10g, MySQL
ERP System : SAP-Sales and Distribution
Operating Systems : MS Windows 95/NT/2000/XP/Vista/7/8/10, MS-DOS, UNIX
Home: Skills
Home: Projects
Movie Recommendation System
Recommendation systems are the systems that helps users discover the items they like.They are widely used across multiple businesses such as E-Commerce, Media, Food, Social networks.Most companies care about recommendation systems to provide better customer experiences i.e helps in speed up the search processes by accessing to the appropriate content, it also helps customers in discovering new items and recommend personalized items that they may like basing on their preferences.
In this Project, we propose a model for the interaction between the recommendation system and users . Each user selects one of the items the system recommends, and reports their experience to the platform by providing a rating as feedback. The platform uses this feedback to update the recommendations for the next user.
Any Queries? Feel free to contact me
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