Software Engineer Developer

MADHU PRIYA MEDA

Mail: ****************@*****.***

Ph: 361-***-****

Software Engineer

Summary:

Full Stack Software Developer with 3+ years of in-depth experience in crafting high-performing web applications across a broad spectrum of technologies, including Java, Python, Spring, Angular, and React. Proficiency in the entire software development lifecycle—from initial concept through to design, development, and deployment. My expertise includes seamlessly integrating sophisticated backend architectures with intuitive front-end frameworks. Skillful in leveraging cloud technologies, particularly AWS, and proficient in executing CI/CD pipelines to enhance development efficiency.

Technical Skills:

Programming Languages

Java, Python, SQL, JavaScript, Scala

Frameworks & Libraries

Spring, Spring Boot, Hibernate, TypeScript, PostgreSql,Angular 7/8, ReactJS, NodeJS, Struts, JUnit, Selenium, Kafka, Groovy, Microservices

Databases

MySQL, MS SQL Server, DynamoDB, MongoDB, Oracle, Redis, NoSQL, CQL

Cloud Technologies

AWS (EC2, ECS, S3, Lambda, IAM, CloudWatch), PCF

DevOps & Tools

Jenkins, Git, Bitbucket, GitHub, Kubernetes, Docker, Terraform, Apache Tomcat, Apache, SourceTree, Confluence, Ant, Maven, Gradle

Development Practices

TDD,, CI/CD, SCRUM, Agile

Web Technologies

HTML, CSS, Bootstrap, AJAX, JSP

Software Engineer at AT&T (10/2023 –Present)

Developed robust Java applications using frameworks like Struts and Spring, applying design patterns such as Singleton and Builder for optimal code maintainability and scalability.

Engineered RESTful services using Spring Boot, enhancing system scalability and performance, tailored to high-load environments.

Analyzed 150+ applications and requirements from Wiki’s and documentation and collaborated with BA’s and QA’s.

Integrated Apache Kafka to facilitate efficient, real-time data processing across distributed event-driven microservices.

Transformed flows with low performance, optimizing workflows by 30%.

Upheld high standards of code quality through rigorous code reviews and TDD practices using JUnit and Selenium, ensuring robust application builds.

Utilized DevOps, agile principles and Jenkins to enable CI/CD. Decreased production time by 40%

Fostered team collaboration and technology adaptation, maintaining high coding standards and integrating cutting-edge technologies such as Docker, Kubernetes, and AWS.

Proficient in a broad range of technologies including Java/J2EE, Spring MVC, Angular 7, MongoDB, and cloud services, using tools like Eclipse and IntelliJ for development.

Environment: Java/JEEE, Spring Boot, NoSQL, Terraform, Docker, IOC, JDBC, XML, Microservice, Spring MVC, Spring Security, REST API, Angular 7, Junit, SQL Developer, Kubernetes, Oracle, CICD, Jenkins, Kafka, Apache, Git, SourceTree, Jira, AWS, EC2, S3, Lambda, MongoDB, Redis, Eclipse, IntelliJ.

Java Developer at Comcast (09/2022 – 09/2023)

Developed high-performance Java applications employing advanced object-oriented design patterns, enhancing functionality and maintainability.

Used Visual Studio Code for effective code editing and debugging, increasing code quality by 40%.

Cut merge conflicts by 13% using Git for version control and collaboration.

Improved database performance by optimizing MySQL queries, boosting query response times by 20%.

Executed complex SQL and NoSQL database operations, seamlessly integrating these with applications for robust data handling.

Developed interactive web applications using React.js and Node.js, ensuring high responsiveness and user engagement.

Designed responsive front-end interfaces using AngularJS, HTML5, CSS3, JavaScript, and Spring frameworks, improving user experience and accessibility.

Managed source control using GitHub and SourceTree; automated build and deployment processes with Jenkins within an Agile development framework.

Leveraged comprehensive AWS cloud solutions (EC2, S3, Lambda) for efficient application deployment and storage, enhancing scalability and reliability.

Environment: Java, J2EE, Spring, Spring Boot, Python, Microservice, Angular 8, Node, React, HTML, CSS, JavaScript, TDD, Junit, SQL Developer, Kubernetes, Oracle, CICD, Jenkins, Kafka, Apache, Git, SourceTree, Jira, OpenText, Confluence, AWS, MongoDB, Redis, Eclipse, IntelliJ.

Associate Engineer at DXC Technology (11/2020 – 07/2021)

Implemented scalable multi-threaded RESTful services using Spring Boot, enhancing system responsiveness and throughput.

Developed intuitive user interfaces with modern web technologies including HTML, CSS3, Bootstrap, AngularJS, and ReactJS, focusing on seamless user interaction.

Engineered MongoDB data management solutions through custom Data Access Object (DAO) layers, optimizing data retrieval and storage.

Applied Python in AI and ML projects, contributing to data-driven decision-making and automated processes within the development team.

Configured and maintained robust CI/CD pipelines using Jenkins, supporting consistent application deployment and integration practices.

Ensured development adhered to TDD methodologies with JUnit and Selenium, maintaining high-quality code standards.

Orchestrated application deployment and management using Kubernetes and facilitated efficient data handling and streaming with Apache Kafka.

Environment: Java, J2EE, Spring, Spring Boot, NoSQL, Python, Docker, IOC, JDBC, XML, Microservice, Spring MVC, Spring Security, REST API, Angular 7, Node, React, HTML, CSS, JavaScript, TDD, Junit, SQL Developer, Oracle, CICD, Jenkins, Kafka, Apache, Git, SourceTree, Jira, OpenText, Confluence, AWS, EC2, S3, Lambda, Elastic Beanstalk, MongoDB, Redis, Eclipse, IntelliJ.

Projects

Natural Language Processing (NLP) Project

Semantic Text Similarity Tool Master's Thesis, Texas A&M University, 2021-2022

Developed an NLP tool using Python and Natural Language Toolkit (NLTK) that measures the semantic similarity between texts.

Implemented advanced NLP techniques such as tokenization, lemmatization, and word embeddings with Word2Vec to accurately parse and compare textual data.

Engineered and trained machine learning models to classify and rate text similarity, achieving a 95% accuracy rate on standard datasets.

Optimized algorithms for real-time processing of large datasets, enabling the tool to be used in commercial applications such as content moderation and academic research.

Collaborated with a team of researchers to integrate this tool into an educational platform, enhancing the ability to detect plagiarism and assess student submissions automatically.

Extracurricular Activities

Organized computer science Club by engaging in discussion with technologies and participated in the coding challenge.

Volunteer, Tech for Good Initiative by contributing to coding workshops for underprivileged youth, promoting tech education.

Education:

Texas A&M University

Masters of Science in Computer Science - 2022

Kalasalingam Academy of Research and Education

Bachelors in Computer Science and Engineer - 2021

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