You’ll use your skills to help solve real-world problems, while learning about the food, consumer products, and personalized nutrition ecosystem
You’ll work across the Pinto Web stack using tools and languages like JavaScript/TypeScript, Node.js, MongoDB, GraphQL, React, Sass
You’ll envision and create new features for our core data platform, which processes large, complex data sets from a variety of sources
You’ll build interfaces and tools to display, process, and update data on the Pinto platform
You’ll envision and create tools that contribute to and enhance our end-to-end data pipeline
You’ll automate and handle the life-cycle of systems and platforms that process our data
You’ll model, design and implement complex data integrations with our industry partners
You’ll build tools and processes that enhance our end-to-end data pipeline, and will envision new features to continually improve and refine this pipeline
You’ll work with our Research, Nutrition, & Data Analyst teams to gain a deep knowledge of underlying use cases in food data and nutrition
You’ll contribute to the ongoing evolution of the Pinto Web stack

5+ years of professional software development experience
Strong experience with: React, Node.js, document databases (e.g. MongoDB)
Bachelor's degree in computer science (or similar) or equivalent practical experience
A track record of shipping high-quality software from start to finish
A solid foundation in computer science fundamentals with sound knowledge of data structures, algorithms, and system design
Comfortable in a fast-paced startup environment
Self-aware and have a desire to learn and improve
Example of code projects you’ve worked on (e.g. GitHub, BitBucket)
Experience with: TypeScript, Amazon Web Services (AWS), Distributed Systems
Experience working with React Native
Experience working with large, complex data sets from a variety of sources
Experience with or strong interest in data science and/or machine learning
Strong communication skills

Senior Full Stack Software Engineer

Key skills