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Gavin Carew

Back-End Engineer
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About me

Back-end developer with an interest in data engineering. I've made some cool API's and monolithic apps. While my specialty is Ruby/Rails, I know just enough Python to be dangerous. I like working with PostgreSQL databases best, but have made apps with other SQL databases as well. I love high-level software design and architecture, and am a firm believer that strong design and continuous refactoring inevitably pays off.

I consider myself a lifelong learner.

I started working into accounting when the company I was working for after moving home from college had an AR position open up. I found I had a knack for accounting, but not a passion. The part of the job that I really liked was financial modeling. It allowed me to continue to improve the foundational skills I had set up while working on quantitative modeling in the biology lab in college.

This led me to take a course in data analytics at UW, where I found that I have a strong interest in big data and data science. In July of 2022 I took the plunge and enrolled in the Turing School of Software and Design in the back-end engineering program. It's an intense course, but I am learning so much every day. And at the end of the day, that's what I love most.

Preferred locations

  • Denver, CO
  • Salt Lake City, UT
  • Seattle, WA
Open to other locations and/or remote work

Previous industries

  • Accounting

Skills

  • Bootstrap
  • GitHub
  • PostgreSQL
  • R
  • Rails
  • Ruby
  • SQL

Currently learning

  • Django
  • Python

Projects

Viewing Party

Viewing Party

Project scope time 35 hours
Collaborators Profile picture for Alaina Kneiling

Tools Used

  • Bootstrap
  • Rails
  • Ruby

Viewing Party is a paired project where a user can create an account, search for a movie, and invite their friends to view the movie together at a specific date & time. It includes a Bootstrap frontend.

Launch the App Code Repository
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Flakes of Wrath

Flakes of Wrath

Project scope time hours
Collaborators Profile picture for Noah van Ekdom Profile picture for Kaelin Sleevi Profile picture for Ryan Smith

Tools Used

An app to Plan winter trips into the backcountry with smart forecasts and a proprietary avalanche prediction algorithm. This is an idea I had before starting at Turing that was made a reality with the help of an amazing team of coders.

Built with a Service Oriented Architecture with Rails for both the front and back ends. All endpoints are restful, and the backend uses a service-facade design pattern. Authentication is through Google OAuth. We used Bootstrap with some custom CSS to make it pretty. It's currently deployed to fly.io.

The main product is an avalanche forecast that combines current avalanche conditions from the Northwest Avalanche Center with a 7-day forecast. Additional features include setting a favorite zone, planning future trips, and adding emergency contacts. All endpoints have full CRUD functionality.

Flakes of Wrath was selected for Demo Comp to represent the 2207 back-end cohort.

Launch the App Code Repository
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Eat and Educate

Eat and Educate

Project scope time 25 hours
Collaborators

Tools Used

  • GitHub
  • PostgreSQL
  • Rails
  • RSpec
  • Ruby
  • SQL
  • Visual Studio

RESTful rails API for a frontend that allows users to find recipes from a certain country along with learning resources for that country. Also uses a service-facade design pattern

The core of the API is combining multiple external API calls (Edamam, Unsplash, Youtube, GeoAPIfy Places) into one serialized JSON package to be sent to the front-end. Users can also favorite recipes and perform fuzzy searches. 100% tested with RSpec, with Webmock and VCR to intercept HTTP requests. Not included in the repo is a full Postman test suite for every endpoint.

This project includes full encrypted authorization.

Code Repository
Screenshot detail for project Eat and Educate

Rails Engine

Rails Engine

Project scope time 24 hours
Collaborators

Tools Used

  • PostgreSQL
  • Rails
  • RSpec

A RESTful rails API to allow a client to query merchant and item data. Mock data is stored in a Postgresql database. Includes search functions by name and price parameters. Created in a five day sprint. See the Github README for more details.

Code Repository
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