Full Stack Developer with 8 years of experience
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Zig
NoSQL
FastAPI
Git
Vue
Linux
C++
IAM)
CloudSearch
MacOS
Rust
AWS (EC2
Tailwind
Phoenix
Ruby
C
Go
MySQL
ElasticSearch
Python
Rails
Docker
MongoDB
RDS
Sinatra
Elastic Beanstalk
PostgreSQL
- 8 years of professional development experience as a full stack developer. Most familiar (use most days): Python, FastAPI, Ruby, Rails, Sinatra, MySQL, PostgreSQL, Linux, MacOS, Docker, AWS (EC2, RDS, Elastic Beanstalk, IAM), Git. Familiar (Use most months): ElasticSearch, CloudSearch, Tailwind, Vue. Hobbies (Used on at least one completed project over the past five years): Go, Zig, C, C++, Rust, Phoenix, NoSQL, MongoDB (probably more, but these were the ones that came to mind.) My day job has me performing two main functions: - Building full stack web development systems. I generally lean more towards writing backend code, and documenting our infrastructure. UI is my weakest area. This role has me working in datasets with ~1 billion row tables, and search indexes with ~100 million documents. Since we're a small company (~8 developers), I have been a major part of the architecture of our systems over the past 8 years. We've got five separate core businesses that our dev team supports, and I've been a part of architecting and implementing all of them. I would prefer to focus more on backend development in a future role. - Creating one-off scripts or processes to assist in business functions. These tend to involve quickly reverse engineering undocumented web APIs we have permission to use, and querying them for our customers. At their simplest, these are a mix of writing some SQL and a few HTTP requests. At their most complicated, they have involved designing and implementing a tree structure to accurately model the business domain, and then pulling data about these structures from relevant public APIs. This month, I reduced the cost of a company's AWS CloudSearch spend by 80% (over 10k/month) by reviewing their codebase, doing some research, and improving what they were storing and how they were doing so. This required a one-line code change on the existing codebase, and writing a new, short (~500 line) indexer. Doing a deep dive into the single highest AWS line item was the impetus for the project, and frankly, it turned out far better than expected. Outside of work, I run https://www.thiswebsitewillselfdestruct.com, a website I built and maintain. It really will self-destruct, and it reaches ~100k users and handles ~13M requests each month. Building tools and infrastructure to manage its moderation and keep it a positive community has been a huge learning experience.