Candidate Information | Title | Salesforce Developer Application Development | Target Location | US-MI-Detroit | Email | Available with paid plan | | 20,000+ Fresh Resumes Monthly | |
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| | Click here or scroll down to respond to this candidateEducationWork HistoryEMAIL AVAILABLE http://LINKEDIN LINK AVAILABLE +1 (Street Address ) 381 0981 Cincinnati, Ohio EMAIL AVAILABLE http://www.linkedin.com/in/Parameswara-palle Application Development Analyst at AccentureJul Street Address Jul 2023 Accumulated 2 years of proficiency in the development and administration of Salesforce B2B Commerce Cloud and Service Cloud, specializing in Apex customization, triggers, test classes, and batch processing, showcasing strong problem-solving and technical expertise. Orchestrated the integration of a state-of-the-art settlement engine to streamline payment processing operations, ensuring seamless fund transfers from outlets to Coca-ColaStreet Address ;s financial systems; enhancements led to a 30% reduction in payment processing time and increased accuracy in fund transfers by 20%, highlighting effective leadership and attention to detail. Worked on B2B Commerce Cloud (Cloud Craze) with experience in configuring new Storefronts and related admin tasks, demonstrating adaptability and strong collaboration skills. Demonstrated the ability to adapt in Agile environments for 2 years, using SCRUM & SAFE methods to make sure projects aligned with business goals. Successfully integrated third-party applications from AppExchange, such as GitHub, to enhance Salesforce functionality, emphasizing innovation and resourcefulness. Executed Salesforce configuration tasks, including creating applications, objects, relationships, layout design, and 15 workflow rules, enhancing system usability and scalability. Actively involved in Lightning Web Components (LWC) and Lightning Flows, continuously enhancing and customizing Salesforce for improved user experiences and efficiency and maintaining 85% test coverage for all the classes as per client requirements. Implemented & customized Salesforce Field Service Lightning (FSL) solutions to optimize mobile workforce operations, including configuring service territories, resources, work types, and scheduling policies, resulting in improved service efficiency & customer satisfaction. Software Internship at SenpiperJun 2020 Jun 2021 Operated within the Ubuntu environment, honing Java skills while working on the Spring MVC framework and SQL database. Managed Flosum migration between Dev, QA, and UAT, ensuring a seamless transition and data integrity, resulting in a 10% reduction in migration errors. Customized 25+ field service app batches to optimize service operations and enhance user experience. Implemented sharing rules, OWD, profiles, roles, and permission sets, resulting in a 15% improvement in data security compliance within the Salesforce platform. Developed 10+ triggers and comprehensive test classes to maintain code quality and reliability, achieving & maintaining 85% coverage. Engaged in Salesforce administration tasks, resulting in a 15% increase in report accuracy and a 20% improvement in user dashboard usability.WORK EXPERIENCE Salesforce Certified Platform App Builder Salesforce, Business Logic and Process Automation, Data Modelling and Management Salesforce Admin Certification Configuration & Setup, Object Manager & Lightning App Builder Salesforce Platform Developer Salesforce, Apex, Java CERTIFICATIONS Languages: Java, Apex, C++, Python, JavaScript Databases: SQL, SOQL (Salesforce)SKILLS Back-End Frameworks: Spring Boot Front-End Frameworks: Aura (Salesforce), Salesforce Lightning Object Tracking and Handwriting Prediction Deep Learning, Image Processing Built a real-time object tracking system utilizing a laptop webcam & color-based object detection to capture data written in air.Employed bitwise operations for effective data storage and continuous tracking of the object.Utilized Convolutional Neural Networks (CNNs) for handwriting prediction, enhancing model accuracy to 98%. Thresholding-based brain tumor segmentationCollaborated on an algorithm based on color channel information of brain MRI for accurate skull stripping.The implementation of the algorithm took 1.8 seconds and achieved 98% accuracy for tumor segmentation. PROJECTSSep 2017 May 2021Bachelor of Technology in Electronics and Communication Engineering from National Institute of Technology Bhopal, India Aug 2023 Apr 2024Master of Engineering in Computer Science from University of Cincinnati Ohio, USA GPA: 3.91PARAMESWARA REDDY PALLEEDUCATION |