- Email: [email protected] | [email protected]
- Location: Sterling, VA, USA
- GitHub: https://github.com/Fetulhak
- LinkedIn: https://www.linkedin.com/in/fetulhak-shewajo-b467b728/
I am a Full Stack Java Developer with over 3 years of experience in developing enterprise-level applications and microservices using Java, Spring Boot, Angular, React, and AWS. I possess strong expertise in backend development, cloud computing, microservices architecture, and database management. Additionally, I am passionate about leveraging Machine Learning to create intelligent, data-driven solutions.
I specialize in both the frontend and backend aspects of web development, particularly using Spring Boot for backend services and Angular and React for responsive and dynamic frontend applications. I also have a strong focus on cloud technologies, especially AWS, and I actively contribute to optimizing systems and applications for performance, cost-efficiency, and scalability.
On top of my technical abilities, I have a deep interest in Machine Learning and AI. I have worked on medical imaging projects (like malaria parasite detection and cervical cancer screening) and have experience in using deep learning models like CNNs, RNNs, and LSTMs for various AI-based tasks.
Over 3+ years of IT experience as a Java Full Stack Developer in the areas of Analysis, Design, Development, Testing, and Deployment of web-based and client-server multi-tier applications. I have hands-on experience in developing applications using Java, Spring Boot, Microservices, JSP, React, Angular, AWS, Docker, Kubernetes, and CI/CD pipelines. My goal is to contribute to innovative, impactful projects by applying both my web development and machine learning expertise.
- Java 8+, Spring Boot, Microservices, Spring Security, Spring MVC, Spring JPA, Spring Data, Hibernate, JPA, RESTful APIs, JSP, JSF, React JS, Angular 6/8, Vue.js, Node.js, Express.js, Docker
- Amazon Web Services (AWS): EC2, S3, Lambda, CloudFormation, CloudWatch, RDS, Redshift, CodePipeline
- Containerization: Docker, Kubernetes
- CI/CD Tools: Jenkins, GitLab CI, AWS CodePipeline
- Version Control: Git, GitHub, Bitbucket
- Relational Databases: MySQL, PostgreSQL, Oracle
- NoSQL Databases: MongoDB, Cassandra, CouchDB
- Message Brokers: Kafka, RabbitMQ
- Deep Learning Frameworks: TensorFlow, Keras, PyTorch
- Machine Learning Algorithms: CNN, RNN, LSTM, GRU, SVM, Logistic Regression
- Libraries: scikit-learn, NumPy, Pandas, Matplotlib, Seaborn, OpenCV
- Tools: Jupyter Notebook, Google Colab
- Frontend: HTML5, CSS3, JavaScript, TypeScript, React JS, Angular 8, Bootstrap, jQuery
- Backend: Spring Boot, Flask, Django, Node.js
- APIs: REST, SOAP, GraphQL
- Other Tools: Postman, Swagger, Apache Kafka, Redis, Elasticsearch
- BSc in Electrical Engineering
- MSc in Computer Engineering
Project: Development of financial services for enterprise solutions
- Developed microservices with Spring Boot, deployed on AWS EC2 using Docker containers.
- Implemented Kafka for real-time data integration, working with Kafka producers and consumers.
- Created Single Page Applications (SPA) with Angular 8 and React JS, utilizing Redux for state management.
- Designed and developed REST APIs for client-server communication, ensuring secure, scalable, and high-performance integrations.
- Optimized AWS Redshift clusters to enhance data storage and query performance, resulting in a 20% reduction in operational costs.
- Created unit tests using Jasmine and Karma for Angular components, ensuring high code quality.
- Leveraged AWS Lambda to automate cloud-based tasks, streamlining business operations.
- Implemented CI/CD pipelines using Jenkins and AWS CodePipeline to automate deployments and reduce manual errors.
Project: Modernization of legacy client-based applications
- Led the effort to modernize the legacy frontend by migrating to AngularJS and utilizing Spring Boot for backend services.
- Integrated SOAP and RESTful web services, ensuring seamless data flow across distributed systems.
- Employed Spring AOP for exception handling and Spring DAO for database operations.
- Optimized SQL queries and implemented database indexing strategies, improving query performance by 30%.
- Built microservices using Spring Boot, creating a robust and scalable system that interacts with various backend systems and external APIs.
- Participated in Agile Scrum methodology, attending sprint meetings, reviewing stories, and helping deliver features on time.
- Malaria Parasite Detection Using CNN: Worked on a Convolutional Neural Network (CNN) to detect malaria parasites in blood samples from images, achieving high classification accuracy.
- Cervical Cancer Screening Using Deep Learning: Used deep learning models to predict the likelihood of cervical cancer from medical images, contributing to improving diagnostic capabilities in healthcare.
- AI-Based Medical Imaging Diagnostics: Developed models for medical image classification tasks such as tumor detection and organ segmentation, leveraging TensorFlow and Keras for deep learning.
- AWS Certified Solutions Architect – Associate
- Machine Learning with TensorFlow on Google Cloud
- Deep Learning Specialization by Andrew Ng
- Certified Kubernetes Administrator (CKA)
- Spring Framework – Full Stack Developer
- CI/CD & DevOps: Jenkins, Docker, Kubernetes, AWS CodePipeline, GitLab CI
- Testing: JUnit, Mockito, Protractor, Jasmine, Karma, Jest, Cypress
- Version Control: Git, GitHub, Bitbucket, SVN
- IDEs: IntelliJ IDEA, Eclipse, VS Code
- Cloud: AWS (EC2, S3, Lambda, Redshift, CloudFormation), Azure
- Web Servers: Apache Tomcat, Nginx, WebSphere
- Project Management: Jira, Rally, Trello
- APIs & Services: REST, SOAP, GraphQL, Apache Kafka
- Containerization: Docker, Kubernetes
- Monitoring: Splunk, Prometheus, Grafana, CloudWatch
- Database Management: MySQL, PostgreSQL, MongoDB, Oracle, Redis
- AI-Powered Web App: Developed a web application to detect emotions from text using NLP and TensorFlow, allowing users to analyze the sentiment of any written content.
- Real-Time Chat Application: Built a real-time chat app using Node.js and WebSocket, allowing users to send and receive messages instantly.
Feel free to reach out for any inquiries related to Full Stack Development, Machine Learning, AI, or any other innovative technology project. I am open to collaboration, mentoring, and discussing potential opportunities to work on impactful solutions.
When I'm not coding or diving into machine learning models, you can find me exploring new technologies, contributing to open-source projects, or hiking in nature.