Trung Vu
Full stack software developer
Email: info at dtrung dot com
Resume available upon request
Web: https://dtrung.com
Blog: https://dtrung.com/blog
Introduction
Trung Vu is a software professional with a decade of experience ranging from building scalable and performant backend services to developing single page application in latest JS frameworks.
Currently he is a senior software engineer at Dosh where he builds massively scalable microservice architecture using AWS Lambda and serverless technology. Technology stack includes Node, Lambda, Serverless, GraphQL, Kinesis and RDS, etc…
From Jan 2016 to Oct 2017, he was a tech lead at Snap Kitchen where he architected and developed backend system in Python, flask, PostgreSQL and Kafka. He also designed, implemented and brought to production Snap Kitchen first data pipeline using Apache Kafka to move large amount of data between systems. The technology platform allow Snap Kitchen grow its digital avenue from $0 to $7 million run rate 6 month after launching its first iOS app
From April 2013 to December 2015, Trung Vu was a tech lead at The Zebra where he developed and lead development of all of its projects including the insurance estimate comparison backend, its SPA front end client, back office system and a mobile web application. Technologies used includes Python, Django, Celery, React, KnockoutJS, etc…
Prior to The Zebra, Trung Vu held a full time position as Software Developer II at HomeAway Inc in User Management System where he designed and implemented Single Sign On system for HomeAway and its 17 websites. Technologies used includes Java, Spring Framework, MyBatis, Maven, etc…
Trung Vu received a bachelor and master degree in Computer Science from the University of Texas at Austin
Employments
11/2017 – Now
Senior Software Developer @ Dosh
Architected and implemented Dosh’s effort in rewriting a large part of its beta product into a scalable, resilient and stable micro-service running on AWS Lambda. Instituted best practices in developing production ready micro-services including:
- Linting with ESLint
- Unit and integration tests with Jest
- Secured configuration with AWS Parameter Store that support at rest & in transits encryption
- CI/CD with CircleCI
- Performance monitoring and logging
Created a Yeoman generator that allow Dosh developer to create new services with best practices consistently in 5 minutes from hours.
Wrote plugin for Serverless framework to manage database migration during continuous deployment which prevents developers from running manual and error-prone migrations
1/2016 – 10/2017
Tech lead @ Snap Kitchen
Architect and develop API from the ground up providing e-commerce and personalization for iOS and web client using Python, Flask, Docker and AWS
Research and implement data streaming platform that reliably and scalably move data between widely different systems ranging from Point-of-sale software, PostgreSQL to Excel files.
Act as Quality engineer and set up automation solution with Runscope to functionally test the API periodically and upon each deploy
4/2013 – 1/2016
Technical Lead @ The Zebra
Led the development of The Zebra mobile website, a single page app optimized for mobile conversion using React and Flux. The redesign app increase conversion by 100%
Led a team of 4 developers to develop internal rating application. Cut time per lead from 30 minutes to 5 minutes.
Architected and developed Estimate API that retrieve and index estimates from 3rd party provider [Python, Django, MongoDB, PostgreSQL, Javascript, Knockout, ElasticSearch, RabbitMQ, AWS]
4/2011-12/2014
Founder @ Job Board Cloud
Developed social network Javascript plugins to help job board users find company insider connections within their LinkedIn network. [Javascript, Ruby on Rails, PostgreSQL]
Provided the software as a SaaS solution for job boards. Customers include one of the largest healthcare job boards in the country
Skills
Programming Languages
Web Development
Data Science
Education
2006-2010
The University of Texas at Austin
BS and MS in Computer Science
Udacity
Machine Learning Nanodegree
Coursera
Machine Learning – Stanford
Data Science Specialization – Johns Hopkins