Development Engineer Software

Pranay Prashant Rao

Seattle, USA +1-682-***-**** ***********@*****.***

SUMMARY

Software Development Engineer with proven expertise in designing scalable, high-performance services using Java, RESTful APIs, and agile methodologies. At Amazon, engineered solutions that boosted processing efficiency by 30% and optimized operational reliability across global markets. Demonstrates strong problem-solving skills and effective CI/CD management to ensure robust, continuously improving systems.

TECHNICAL SKILLS

• Programming & Development: Java, JavaScript, TypeScript, Python, Angular.js, Node.js, Flask, Laravel

• Software Design & Methodologies: Object-Oriented Design, RESTful web services, Service-Oriented Architecture, multithreading, agile engineering practices, JUnit, Mockito, TestNG

• DevOps & Infrastructure: CI/CD pipelines, Bash Scripting, Kubernetes, AWS Fargate, Infrastructure-as-Code, ETL pipelines, application monitoring tools, Git

• Databases & Cloud: SQL, MySQL, Redis, firebase, NoSQL databases, DynamoDB, Cassandra, IBM cloud, Azure, AWS

• Other Tools & Technologies: HTML, CSS, Bootstrap, JSON, XML, Eclipse, VS Code, IntelliJ, WordPress, PowerPoint EXPERIENCE

Amazon Feb 2022 - Present

Software Development Engineer Bellevue, WA

• Developed Assignments v2 using Java and Object-Oriented Design principles, employing the Hungarian algorithm to optimize driver-to-route assignments across North America, Europe, and Japan, contributing to monthly profits of $500 million.

• Enhanced RESTful web service APIs by refactoring Java service implementations with a Service-Oriented Architecture approach, improving processing efficiency by 30% and reducing latency.

• Initiated the Quick Assign project to enable DSPs to manage assignment overrides, increasing operational flexibility and supporting agile engineering practices for rapid issue resolution.

• Mitigated high-severity incidents by deploying hotfixes and managing system issues, resulting in a 40% reduction in incoming tickets and a 20% improvement in driver assignment success rates.

• Engineered an integration test framework utilizing TestNG and Hydra for comprehensive CRUD operations, reinforcing robust testing and CI/CD pipeline methodologies.

• Conducted load and stress testing with Hydra, TestNG, and Amazon CloudWatch to identify vulnerabilities and implement optimiza- tions that enhanced system resilience and decreased response times by 20%.

• Streamlined AWS infrastructure with effective resource allocation strategies, contributing to a 15% cost reduction while leveraging Infrastructure-as-Code principles.

• Facilitated sprint planning and backlog grooming sessions to expedite resolution of on-call tickets by 30% and ensure consistent service performance.

• Mentored team members through code reviews and design discussions, fostering professional growth and collaborative development.

• Designed and executed functional and performance tests with AWS, TestNG, and Hydra, automating key processes and improving testing efficiency by 40%.

EDUCATION

University of Texas at Arlington Jan 2020 - Dec 2021 Master of Science, Computer Science

• GPA: 3.7/4.0

PROJECTS

E-Commerce Website using MVC Architecture

• Designed and developed a comprehensive online shopping project for a furniture company.

• We used the agile methodology by considering the requirements and designed the website.

• The authentication and authorization were done using Spring Security. Breast Cancer Classification

• Implemented ML model to classify patient into malignant and benign for breast cancer to help in early diagnosis of breast cancer which can improve the chances of patients getting good treatment from the beginning and thus increasing chances of their survival.

• Developed and trained several machine learning models - Random Forest, SVM and chose Random Forest classifier as a best model with 95.50% accuracy and 96.57% precision.

PUBLICATIONS

• Structuring and Design of Home Automation System using IOT. in IJRTER Volume 4, Issue 5; ISSN: 2455-1457.

• Counterfeit Currency detection and Classification. in IJIRSET, Volume 6, Issue 11, ISSN: 2319-8753.

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