ABOUT ME

I am a software engineer with over 4 years of development experience seeking new opportunities. Having built up a strong foundation in programmable logic and data structures, I specialize in Automation, Predictive Analytics and Full Stack development. I love the combination of creativity and problem solving skills used when writing code and I'm always looking forward to learn more.

In addition to my education, my past work experience has provided me with the opportunity to build many strengths. 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.

EDUCATION

Bachelor of Computer Science

Wilfrid Laurier University

September 2015 - April 2019

Big Data Concentration

EXPERIENCE

S&P Global - Software Engineer

September 2022 - Present

Built an automated testing suite with TestCafe, reducing QA time by 96% and accelerating releases by 75%.
Created CI/CD pipeline with Jenkins to automate processing of daily insight files, achieving 100% workflow streamlining.
Led a team of 5+, increasing productivity by 40% & cutting delivery time by 30% through mentorship and Agile practices.
Created options trading experience using Vue, allowing user management of call/put options, increasing trades by 30%.
Developed REST APIs in TypeScript for trading platform to process trade orders in real time, reducing latency in data retrieval, enhancing scalability for microservices, and improving load handling capacity, supporting up to 3x higher traffic.
Containerized microservices using Docker for consistent deployments across environments; used Nomad for automated scaling and orchestration, reducing downtime during traffic peaks and optimizing resource usage by 25%.

Trexity - Software Engineer

August 2021 - August 2022

Developed features for web and mobile apps using TypeScript, Node, React/React Native, Firestore and PostgreSQL.
Architected scalable NoSQL database solutions using Google Firestore, optimizing real-time data retrieval and synchronization for the merchant dashboard, resulting in a 40% improvement in data query performance.
Introduced merchant dashboard feature to track driver location, increasing delivery quality and accuracy from 80% to 93%.
Implemented REST APIs using Node.js and Express to create plugins for Shopify and WooCommerce platforms, enabling merchants to integrate existing storefronts with Trexity merchant portal, achieving 90% adoption rate among new users.
Designed and developed system to display routes based on driver’s vehicle specifications, allowing support and drivers to determine if driver’s vehicle can handle delivery volume of route, reducing large volume route renounces by 80%.

Parker-Hannifin - Software Engineer

May 2019 - June 2021

Created and maintained scalable web applications using ASP.NET, C#, SQL, JavaScript and Angular.
Led execution & development of warehouse management system saving over $5,000 and 100 hours of manual labour.
Outlined and corrected points of inefficiency within supply chain, saving over $110,000 and 1000 hours of labour annually.
Developed support chatbot to support over 1000 vendors, reducing email inquiries by 75%.

Amazon - Software Engineer Intern

May 2018 - August 2018

Streamlined order tracking and shipment process flows by automating various metrics reducing QA audits by 85%.
Architected program that finds smaller misplaced products in larger bins, saving over $1000 monthly.
Designed and maintained programs using VBA, increasing productivity in fulfilment centres by 40%.
Engineered automation that keeps track of unfulfilled orders, reducing backlog and mandatory overtime by 60%.

SKILLS

Backend

.NET Core

Django

Express.js

GraphQL

Node.js

Databases

Firestore

MySQL

PostgreSQL

SQL Server

DevOps & Cloud

AWS

Docker

GCP

Jenkins

Kubernetes

Nomad

Frontend

Angular.js

Next.js

Pinia

React.js

Svelte.js

Vite

Vue.js

Languages

ASP

C++

Java

JavaScript

Python

SQL

TypeScript

Testing

Jest

Testcafe

PROJECTS

Film Finder, see more

Python web application that makes rating predictions and recommends movies to user based on user's preferred genre and search history by using Pandas API and SciKit-Learn API.
Designed collaborative filtering algorithm to find movies based on user’s preference and movie’s ratings.
Implements web-scrapper tool that scrapes meta data from IMDB top 100 movies and imports data to MySQL database, which is updated every month.

Laze, see more

Web application where users can “pin” points of interests given their current location within the Wilfrid Laurier campus. This app uses metadata to generate a heat map and showcase active common areas based on user’s pins, displaying information such as study hall availability, Tim Horton’s lineup length, etc.; implemented using Django and Python and MySQL.

Fireflies By Laboni, see more

E-commerce web application for small retail business with recommendation algorithm to enhance user engagement.
Automated key backend processes using AWS Lambda, and integrated S3 to reduce execution time for critical tasks.

CONTACT

Github