I am a software engineer sepcializing in Data and Cloud development using Python and Java. I am a certified AWS Solutions Architect.I love the combination of creativity and problem solving skills used when writing code and I'm always looking forward to learn more.
I'm a natural leader with strong analytical skills which I use to make sound decisions. A positive environment with an emphasis on passion and collaboration is one in which I thrive.
Architected custom GitHub Copilot prompt configurations across all internal repositories, automating README generation and technical Q&A to accelerate developer onboarding
Led migration of national scale payment infrastructure to JDK 21 and Spring Boot 3.5, leveraging Virtual Threads to enhance concurrency and throughput for real-time transactions
Reduced DB load by 25% via EhCache implementation and JPA projection optimization across 600+ files, elimi- nating redundant DAO overhead and improving response times
Developed a real-time detection layer for blacklisting high-risk accounts and emails, integrating service logic with Spring Data JPA for instantaneous transaction blocking
Engineered an asynchronous Scoring Engine retry layer using Spring Async and ActiveMQ, ensuring non-blocking processing and high-availability persistence for risk audits
Facilitated onboarding sessions for new team members, conducted training sessions on Kafka, API development, and best practices to enhance team skills and knowledge
Automated Kafka consumer lag monitoring and configurations for high-throughput streaming pipelines, reducing lag by 30% in high-availability environments
Collaborated with DevOps to automate deployment for 50+ ML data connectors using Jenkins and OpenShift, enabling real-time model inference at scale
Executed zero-downtime, multi-terabyte production data migrations on AWS while optimizing security and performance for real-time enterprise inference engines
Developed a Spring Boot data switch for 30+ REST APIs to allow seamless read-switching between MongoDB and Oracle, resulting in a 25% improvement in average response times
Developed Kafka connectors to facilitate efficient and reliable data communication between different components of the system
Developed classification rules within payment engine using Java causing an increase in the overall success rate of high value payments from 86% to 90%
Improved name matching rate from 8 hours to 2 hours within payment hub by implementing fuzzy string matching algorithm
Created dashboard for analyzing and visualizing payment metrics such as success rate, uptime, fraud rate, etc. using Python, MySQL and PowerBi
Used python to setup ETL pipeline for report processing, reducing data processing time from 1 hour to 5 minutes and used SFTP to automate report email distribution
Built a high performance dashboard that uses a random forest trained on historical data for real-time sports data modeling to give go/no go recommendations for base stealing
Built a movie recommendation system with Jupyter that uses a SVD and collaborative filtering approach to find latent vectors from the Movielens 100k dataset, which are then used by the model to make rating predictions and recommend unseen movies
Wrote an image processing and classification library in Python that applies various filters on images such as scaling, sharpening, etc. using convolution matrices and classifies digits using feature vectors and connected components