At Plastiq, we offer an engineering culture that’s diverse, supportive, and high-energy. We provide people with the opportunity to thrive in an environment that unlocks their maximum potential. We believe in breaking barriers, embracing failure, and challenging ourselves to do what others have told us we cannot. That means learning and growing together and challenging each other to be better engineers and humans.
You will help with work breakdown, execution, and delivery for medium to large projects. This means helping with enforcing performance, security, and architectural standards. You will collaborate closely with product and design teams to deliver best in class experiences to our end users. You are a key technology reference within our product engineering team and you’ll play an important role in ensuring the scalability of our tech that drives our business, product, and platform.
- Architect reliable, high performant, and scalable React Native applications
- Design and code with architectural level considerations in mind, including simplicity, extensibility, testability, resiliency, performance, and security
- Define technical vision for the mobile team and collaborate closely with product, design, and other engineering teams to deliver best in class experiences on the mobile app to our customers
- Articulate alternatives across both new and proven technology solutionsIdentify areas of improvement and drive React Native best practices
- Help to keep the mobile app and information secure at all times, complying with the latest security standards
- Hands-on development of code, complete with automated tests that are scalable and maintainable
- Perform code reviews with helpful and meaningful feedback for your teammates
- Set the bar for documentation, coding standards, security, performance, maintainability, resiliency, reliability, testing, and production visibility (logging/monitoring/alerting)
- Own what you build in production and be an ambassador of Quality
- Actively troubleshoot and resolve production issues
- Mentor and unblock other engineers on the team
- Set the bar for documentation, coding standards, testing, and production visibility (logging/monitoring/alerting)
- Promote efficiency, predictability, and scalability by leveraging tools, frameworks and processes.
Your Minimum Required Experience
- 10+ years of professional software development experience which includes 5+ years experience creating and supporting highly interactive data driven applications
- 5+ years of experience leading technical projects and teams
- 3+ years of hands-on experience in developing and shipping production-level React Native applications
- Ability to make recommendations on the right approach by using various React Native components
- Deep understanding of native Android and iOS and able to leverage native APIs for deep integrations with both platforms
- Experience with MobX/Redux for state management
- Familiarity with native build tools such as XCode, Gradle, Android Studio
- Familiarity with mobile app CI/CD practices
- Understanding of REST API, and Node.js
- Understanding of mobile app security threats and ways to mitigate them
- Familiarity with Push notifications
- Experience with automation tests for React Native apps
- Familiarity with app store submissions, monitoring and managing apps in a production environment
- Have debugged and solved performance issues in React Native
- Demonstrated clear communication skills both written and verbal
Plastiq’s Tech Stack
- Plastiq operates a CI/CD model and releases code to production frequently. We are building cloud-native micro-services with a component-based frontend written in React.js, React Native, and a Node.js backend, which sits in front of our Payments Processing Platform built in Java.
- For our testing platforms we use Jest for API & unit backend tests, cypress.io for frontend testing, and Gitlab for our continuous integration and delivery.
- Plastiq is powered by data. Our data pipeline continuously streams data to Snowflake via AWS Kinesis so our Data Engineering and Analytics team can produce machine-learning models that help drive our business.