I am an accomplished Software Development Engineer and Full-Stack Developer with a Master’s degree in Computer Science from the University of Massachusetts Boston. With over 3.5 years of professional experience, I specialize in building and optimizing robust software solutions using Java, Spring Boot, and AWS.
My background includes significant roles where I've enhanced business processes and improved operational efficiency through innovative technology solutions. As a Full-Stack Developer, I excel in creating dynamic and responsive web applications, leveraging technologies like React and Node.js.
I thrive on creating impactful, data-driven solutions and am currently seeking new opportunities to apply my technical skills and passion for software development to drive meaningful advancements in technology.
I focus on building and maintaining efficient ETL pipelines that transform and load data into databases. Using Python, Pandas, and DBT (Data Build Tool), I work with large datasets to ensure the data is processed accurately and optimized for performance. With experience in SQL Server, I manage databases and streamline workflows, leveraging xAWS cloud services to create scalable, secure solutions.
Along with data engineering, I create dynamic dashboards using AWS QuickSight and Looker to provide clear, actionable insights for business teams. My technical skills, combined with a problem-solving mindset, help me deliver reliable data solutions that drive informed decision-making and improve outcomes.
Engineered an HRMS System using Spring Boot, microservices, and Python-based ETL tools, optimizing employee workflows for a 30% boost in productivity and a 20% reduction in onboarding time. Deployed on AWS (S3, EC2), reducing infrastructure costs by 25% and code execution time by 40%.
Designed data pipelines and ETL processes for SAP B1 mail automation, using Apache Airflow to automate 85% of tasks and reduce processing time by 40%. Leveraged Python, SQL, Apache Kafka, and Spark to handle 50,000+ transactions daily and optimize performance by 30%. Managed MySQL/PostgreSQL databases and utilized AWS (Redshift, S3, EMR) to cut storage costs by 25% and ensure 99.95% uptime.
Full stack development experience with Java, React, and Python, utilizing OpenShift and Kubernetes for container orchestration, and Jenkins for CI/CD pipelines. Improved user engagement by 20% and release frequency by 25% through agile practices.
Crafted comprehensive data visualization, SQL-driven reports and dashboards utilizing Power BI, Tableau, SAP Crystal Reports, and HANA Interactive Analysis. Integrated SQL Server and HANA DB to build interactive dashboards, elevating decision-making efficiency by 30%.
Automated ETL processes using Python, integrating HANA DB and SQL Server into CI/CD pipelines, reducing data processing time by 25%. Developed SQL-driven reports and dashboards, enhancing decision-making efficiency by 30% with Power BI, SAP Crystal Reports, and HANA Interactive Analysis.
Built a high-performance backend for SAP integration with Java and a responsive frontend using React and CSS, increasing system usability by 35%. Designed a dashboard platform that unified SAP modules into a web interface, streamlining operations and improving user experience.
Acquired comprehensive training in web development (Java, HTML, CSS) and mobile app development (Android Studio), with proficiency in MySQL and Firebase for database management.
Developed the Plant Monitor app, using ESP32 and sensors to guide planting times by analyzing environmental data. The app integrates weather forecasts and real-time sensor readings to offer tailored planting advice, secured with advanced encryption.
Developed a Compact Ariel Mapping System using Raspberry Pi, integrating sensors and IR imaging for emergency situation monitoring and individual detection. Utilized Python and OpenCV for real-time data and image analysis, enhancing situational awareness with WiFi signal-based location tracking and a 3D building model updated in real-time using Agisoft Metashape and Unity.
Created "Movie Mate," a genre-based movie recommendation website, using the MERN stack and Tailwind CSS for styling. This web application offers a user-friendly interface with efficient filtering options, utilizing RESTful APIs for seamless interaction and real-time data integration. Features include dynamic movie details, ratings, and personalized recommendations, all enhanced by a responsive design.
The Server Management Tool is a robust mobile application developed using Flutter for a cross-platform interface and a Spring Boot backend. It enables secure server operations, including shutdowns, restarts, and process management, with real-time CPU and storage monitoring. The app features user authentication to ensure secure access and leverages PostgreSQL for efficient data handling, showcasing skills in mobile app development, backend integration, real-time data monitoring, and secure system design.
Led the development of an Android ERP application for an online café, using Java, Flutter, and Oracle Database to enhance operational efficiency. The app features real-time order tracking, automated inventory management, and personalized customer profiles, improving service delivery and customer management through advanced mobile and backend system design.
Developed a web application that explores the historical development of Boston's road infrastructure using React.js, Vega-Lite, and Tailwind CSS. The application offers a responsive and modern interface, featuring interactive data visualizations, historical maps, and detailed narratives about key milestones such as the Boston Post Road and its transformation during the American Revolution.
Developed a real-time stock market simulation system using Python and Kafka, integrated with AWS services like EC2, S3, Glue, and Athena. This setup enables efficient data streaming, robust storage, and advanced data querying capabilities, effectively handling and analyzing high-velocity financial data for real-time insights.
This project harnesses Python and several NLP libraries to perform sentiment analysis on Amazon's extensive food review dataset. Utilizing NLTK's SentimentIntensityAnalyzer for basic sentiment categorization and the cutting-edge RoBERTa model from the Transformers library for deeper analysis, the project classifies reviews into positive, negative, and neutral sentiments. Key features include comprehensive data visualization and comparative sentiment scoring, enhancing the understanding of customer feedback through advanced data science techniques.
Developed an interactive dashboard for UMass Boston, analyzing staff ratings and pay across various departments. This project visualizes key trends and top positions by pay and ratings, offering valuable insights into the university's staffing structure. Built using Google Looker, Python, and pandas, it's an essential tool for educational administration analytics.
Created an interactive dashboard comparing the compensation of coaches and faculty across the University of Massachusetts system. The visualization examines pay trends from 2010 to 2024 and highlights disparities across campuses, offering insights into the salary structures in both academic and athletic roles. Built using Google Looker, Python, and pandas to enhance understanding of compensation dynamics in higher education.