Calvin Leung
Software Engineer
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Software Engineer with 7+ years building reliable, high-scale systems across full-stack web, iOS, and data engineering. Delivered real-time infrastructure, cross-platform apps, and automation tools used across hundreds of clients. Proven track record delivering high-impact features — from real-time chat systems handling millions of messages to iOS manufacturing apps and data pipelines processing 200M+ data points annually.
7+
years experience
5M+
messages shipped
200M+
data points / yr
01
Skills
Programming Languages
Kotlin Python Java Swift Ruby PHP Javascript C# Lua
Web Development
React Node.js TypeScript Javascript Ruby on Rails HTML/CSS Vue FastAPI Flask Django JSON
iOS Development
Swift Flutter Objective-C UIKit SwiftUI Core Data Xcode Core Bluetooth
Databases
PostgreSQL SQLite MySQL MongoDB Redis
Cloud Computing
Docker AWS EC2 ECS RDS VMs VPS Websockets
Networking
RESTful APIs JSON Bluetooth Websockets
Tools
Git VSCode Version Control AI Agile Unit Testing LLM
02
Experience
Software Engineer
Oct 2025 – Present
Workforce management built for the frontline.
- Designed and shipped real-time chat system supporting over 5 million individual messages and led zero-downtime backfill job to migrate historical data
- Led major refactor of timeoff system, delivering critical features with over 90 million entries over 300+ clients. 10x improvement in performance after refactor
- Worked on complex automation system. Enables over 25,000 different automations that unlocks new workflows for customer
- System wide optimizations & bug fixes touching nearly every major product surface. Consistent bug fix and polish work alongside feature delivery (regressions, edge cases, database performance)
Senior Software Engineer
Oct 2021 – Oct 2025
The world's first needle-free continuous glucose monitoring wearable.
- Worked on critical internal web dashboards, allowing teams to monitor and parse millions of data points in real-time across 7+ days.
- Designed and built iOS application for company's manufacturing execution system (MES), enabling teams to track and log every step of the manufacturing process, reducing manual data entry by 10x.
- Developed a scalable and adaptable data pipeline from bluetooth device, to iOS app, to API server capable of ingesting up to 200 million data points a year.
- Collaborated with hardware and data engineering teams to develop a robust protocol for sending real-time data wirelessly between the hardware and iOS app, enabling a 15x increase in data throughput.
- Created a python-based web server responsible for parsing millions of data points and automating tasks performed by the data science team, greatly reducing manual workload for the entire company.
Software Engineer
Dec 2018 – Oct 2021
Cloud Based Social HR Software. From hire to retire in the most advanced way.
- Collaborated with 20+ partner companies to implement cross-platform features and integrations, creating seamless syncing between the two platforms.
- Single-handedly designed, implemented, and deployed company payroll/taxes system for all US and Canadian clients.
- Lead the company in key cybersecurity certifications and implementations, netting the company several key clients.
03
Education
San Jose State University
B.S. Computer Engineering
Dec 2017
04
Projects
Manufacturing Execution System
- Ruby on Rails web app with iOS companion app that tracks medical sensors over its manufacturing from raw materials to finished product, logging fields such as quality assurance checks, batch numbers, operators, and timestamps for each operation.
- Used Ruby on Rails, SideKiq, Redis, Postgres, and SemanticUI for the web app and Swift, SwiftUI, and UIKit for the iOS app.
- Designed the system to handle simultaneous multi-users that redefined the company workflow and boosted manufacturing efficiency, by removing error prone manual steps and replacing them with automated systems.
- Delivered a flexible and robust system adaptable to a dynamic R&D environment while ensuring rigorous quality control for each process in keeping with FDA regulations.
Data Processing Task Server
- Python based web dashboard that analyzed live data to generate detailed charts and graphs, greatly informing the team with real-time results.
- Built with Python, Flask, Celery, Plotly, Numpy, Pandas, and Postgres. And hosted on AWS EC2, allowing users to request charts or calculations through a web API.
- Optimized calculations to process millions of data points concurrently and produce charts in under 10 seconds, with caching of data further reducing response time and load on databases.
- Designed architecture to be fast, flexible and maintainable; making adding or changing the chart outputs trivial and fast, keeping up with a fast R&D environment.