Software Engineer Spring Boot

Sai Sravya Anem Email : *************@*****.***

LinkedIn GitHub Mobile : +1-757-***-****

Summary

Software Engineer with 5 years of experience in developing web applications and microservices using Java, AWS, Spring Boot, and front-end frameworks. Proficient in data analysis, creating data visualizations using Python, JavaScript frameworks. Strong background in developing and integrating cloud based services, deploying infrastructure as code CI/CD pipelines for retail user facing applications. Education

West Chester University West Chester, PA

Masters in Computer Science; GPA: 3.98 Aug 2022 - May 2024 Courses: Web Development, Analysis Of Algorithms, Artificial Intelligence, Machine Learning, Data Visualization, Data Science with Python Gayathri Vidhya Parishad Visakhapatnam, India

Bachelors in Electronics and Communication Engineering; GPA: 4.0 Aug 2015 - May 2019 Skills Summary

• Languages: Java, JavaScript, Python, SQL, HTML, Shell Scripting

• Frameworks: Spring Boot, React, Angular, Selenium, Hibernate, Flask, LangChain

• Databases: MySQL, PostgreSQL, MongoDB

• Tools: AWS, Docker, Bamboo, Jenkins, Kubernetes, Github

• Software Practices: AGILE, Scrum, Bug Tracking, Regression Testing Experience

Prorsum Technologies Exton, PA

Software Engineer Sep 2024 - Current

• Microservices Development: Leveraged Java and Spring Boot to design and implement microservices, while utilizing React to create personalized front-end experiences. Integrated AWS DynamoDB for efficient storage of customer behavior data and employed AWS API Gateway to facilitate seamless interactions between microservices and external APIs.

• Cloud-Native Applications: Engineered scalable, cloud-native applications utilizing Spring Boot and REST APIs. Employed object-oriented programming principles and component-oriented architecture to improve maintainability and performance.

• Containerization: Dockerized the Spring Boot application and stored container images in AWS Elastic Container Registry

(ECR) for artifact management. Provisioned infrastructure using CloudFormation to create and cost effecient web services.

• Security Implementation: Integrated OAuth 2.0 and Spring Security to safeguard customer data and ensure secure access across web and mobile platforms. Automated deployment pipelines using AWS CodePipeline to minimize downtime.

• Continuous Integration: Streamlined the packaging of JAR files using Maven, ensuring compatibility across diverse environments, regions. Configured GitHub Actions to automate builds, code scans, test-coverage with every code push.

• Performance Improvements: Implemented caching strategies using AWS ElastiCache, resulting in a 30% reduction in query response times to retrieve tracking information. Enhanced APIs SLA by 20% using database query tuning. Infosys Hyderabad, India

Software Engineer Aug 2019 - Aug 2022

• Customer Onboarding Solutions: Designed and maintained robust customer onboarding solutions using Java and Spring Boot, achieving seamless integration with Verizon’s retail systems and resulting in a 25% reduction in customer incidents.

• API Development: Developed secure and efficient RESTful APIs to process customer data from retail stores, facilitating smooth data exchange between in-store systems and backend services.

• Microservices Deployment: Leveraged AWS EC2 for hosting microservices dedicated to customer profile creation, enabling auto-scaling capabilities to accommodate peak traffic during promotional events.

• UI Component Enhancement: Created high-quality UI components using React.js and Angular, significantly improving user interface experiences and integrating new business features and apply fixes.

• Database Performance Optimization: Improved the SQL queries performance to enhance retrieval by creating indexes and performing data modeling to efficiently store data in MySQL database.

• Continuous Integration and Deployment: Configured CI/CD pipelines and enabled web-hooks to setup seemless deployment across multiple projects to integrate Docker, Jenkins, GitHub, and JIRA software.

• Automated Quality Assurance: Executed regression testing with Selenium and TestNG, ensuring thorough automation testing. Collaborated within Agile and Scrum frameworks to adhere to monthly release cycles and facilitate iterative deliveries. West Chester University West Chester, PA

Graduate Research Assistant - Prof. Md. Amiruzzaman Jan 2023 - May 2024

• MEAN Stack Development: Developed robust MEAN stack web applications to facilitate comprehensive data analysis, significantly enhancing analytical capabilities and user engagement.

• Machine Learning Modeling: Designed and validated sophisticated machine learning models for financial trend prediction, optimizing accuracy through advanced feature engineering and algorithm tuning. Successfully transformed these models into a web-based dashboard for real-time forecasting, enabling proactive decision-making.

• Data Visualization: Engineered a suite of interactive Tableau dashboards to present complex datasets effectively. Streamlined communication by condensing 30 hours of analysis into impactful visuals that facilitated rapid comprehension and informed strategic discussions.

• Research Documentation: Authored detailed research reports in LaTeX that meticulously outlined methodologies and outcomes. Improved the readability of complex data, enabling the effective distribution of findings to 15+ stakeholders across various departments and enhancing cross-functional collaboration. Academic Projects

• LinkedIn Profile Summarization: Developed a robust LangChain-based application for extracting LinkedIn summaries, significantly improving data retrieval and processing efficiency. Implemented Scrapin.io for accurate and structured extraction of profile information, ensuring high-quality data collection. Designed an interactive dashboard using Flask that provides users with a seamless interface to visualize and analyze the extracted data effectively.

• Forecasting Financial Markets using Machine Learning and Sentiment Analysis: Leveraged Natural Language Processing (NLP) techniques and advanced machine learning models, including XGBoost and ARIMA, to analyze market sentiment and forecast financial trends. Developed a web scraping tool using BeautifulSoup to extract relevant financial news data. Enhanced sentiment analysis accuracy by utilizing the VADER sentiment analysis tool and integrating its results with machine learning models, leading to improved market trend predictions.

• Car Parking Solutions: Engineered a comprehensive car parking management system featuring three distinct user roles to ensure efficient access control and functionality. The system integrates real-time slot booking, allowing users to seamlessly reserve parking spaces. Implemented robust email verification processes to enhance signup security and incorporated email notifications for wallet deductions, providing users with timely transaction updates and improving overall user experience.

• Pharmacy Management System: Designed and developed a web application aimed at streamlining pharmacy employee management, enhancing transaction monitoring for improved tracking and record-keeping. The system optimizes operational efficiency by automating key processes, ensuring accurate data management and timely access to vital information for staff and management.

Honors and Awards

• Verizon – Associate of the Quarter (Q2, Q4 – 2020)

• Best Presenter Award – PASSHE STEM Conference, 2024

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