Software Engineering

Hafeeza Samreen

669-***-**** # *******.*******@****.*** ï Linkedin § GitHub * San Jose, CA Education

Master of Science in Computer Software Engineering Aug 2024 – May 2026 San Jose State University, USA GPA: 4.00/4.00

Course Work: Enterprise Software Platforms, Software Systems Engineering, Distributed Systems, Cloud Computing, Machine Learning, Python Programming, Data Structures & Algorithms, Data Mining, Big Data, Data Visualization, Operating Systems. Technical Skills

Tech Stack: C/ C++/ C#, Java, Python, Go, JavaScript, TypeScript, jQuery, HTML, CSS, PHP, React, Angular, .NET. Cloud and Databases: Amazon Web Services, Azure, SQL, MongoDB, MySQL, PostgreSQL, SQLite, Redis. Infra and DevOps: UNIX/Linux, Microsoft Azure, Kubernetes, Docker, Git, GitHub, Jenkins, CI/CD. Technologies and Tools: Node.js, Spring Boot, Django, Selenium, Shell script, PowerBI, Alteryx, Scrum, Agile. Experience

Software Engineer-II, Deloitte Jun 2024 – Aug 2024

• Upgraded dynamic applications using Angular, leveraging JavaScript for scalable code and RxJS for reactive programming.

• Refined PostgreSQL queries, reducing data retrieval time from 1.2 seconds to 700 ms in high-traffic applications.

• Integrated OAuth 2.0 for secure authentication across multiple web apps, resulting in a 30% increase in security compliance.

• Conducted code reviews, authored technical design documents, and retained technical specifications of product. Software Engineer-I, Deloitte Aug 2022 – May 2024

• Executed migration of .Net applications to Azure Cloud, utilizing Azure App Services and Azure SQL Database, leading to 25% increase in application efficiency and enhanced revenue streams.

• Deployed RESTful APIs to facilitate front-end and back-end communication, limiting response times from 200ms to 150ms.

• Led database upgrades as a rotation resource in the Production team, resolving support requests within tight timelines, resulting improvement in system reliability and decreasing downtime from 10 hours to 8 hours per month.

• Executed Infrastructure as Code (IaC) using Terraform, minimizing manual configuration and standardizing deployments. System Architect Intern, Pegasystems Nov 2021 – May 2022

• Co-developed microservices for stock trading systems using .NET and Kafka for real-time data streaming and improving peak trading efficiency through Pega integration and created performance dashboards in React.js, refactoring legacy services to cloud-native AWS architectures, lowering costs by one-fourth. Software Engineer Intern, Deloitte Jul 2021 – Oct 2021

• Designed a scalable MySQL database schema, optimizing data storage, ensuring seamless integration with backend services.

• Built scalable microservices with Spring Boot and integrated frameworks like Django, boosting system modularity and cutting release times by 25%. Applied CI/CD for testing, defect tracking, and version control using Git to ensure software quality. Software Development Engineer Intern, EPAM Systems Sep 2020 – Jun 2021

• Automated build and deployment pipelines using Jenkins, Docker, and Kubernetes, increasing release frequency from 10 to 13 per month and reducing deployment failures by 15% through scalable micro-service architecture. Projects

Traffic Volume Prediction Platform Python, Flask, React, AWS, Node.js, MySQL, MongoDB

• Devised a Machine Learning-based traffic prediction system, refining forecast accuracy by 20% across 1 million records, supporting 1000 concurrent API requests. Utilized Spring Boot for backend services, MongoDB and MySQL for database management, and Docker for containerized deployment. AI-powered Sentiment Analysis Chatbot Python, TensorFlow, Keras, React.js, Flask, AWS Lambda, Docker

• Developed a real-time chatbot for sentiment detection with 92% accuracy using custom NLP and Machine learning models. Utilized AWS Lambda for serverless architecture, integrating with a Flask API for seamless data handling. Deployed using Docker containers and managed with Kubernetes for scalability. Change Detection for Building Classification Python, Flutter, OpenCV, PostgreSQL, Deep Learning

• Applied ResNet-50 and U-Net CNN models for change detection, improving segmentation accuracy by 15% on over 10,000 high resolution images. Utilized OpenCV for preprocessing, conserving image processing time by 30%. Achievements

• Publications: Real-time Weather Forecast Application Change Detection for Building Classification

• Certifications: Oracle Generative AI Professional Cisco Certified Networking and Python Programmer PEGA System Architect AWS Cloud Computing and Cyber Security Specialist.

• Awards: Q1 FY23 Applause Award - Deloitte Secured 64th rank - Code Innovate Hackathon ’21 Organizer Appreciation Award - Computer Society of India Student Volunteer - National Service Scheme.

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