As a Software Engineer, Full Stack Engineer, you will be involved in both web application and data pipelines development in order to provide high-quality services to achieve business needs. You will focus on architecture, system design, feature implementation, code review, test automation and deployment of new features with high scalability requirement. You will work at Appier Japan in Tokyo, Japan and co-work with teammates in Taipei, Taiwan.
Responsibilities
- Full stack web application and data pipelines development
- Ensure scalability, reliability and maintainability among micro-services
- Design system architecture and apply proper technologies
- Work closely with our PM/ML team to define feature specifications
- Perform code reviews to ensure high-quality and clean code
- Build and maintain unit tests and test automation
- Handle and resolve system and clients issues escalated from operational environment
- Stay on-call for critical alerts in rotation
Requirements
- Resident of Japan or one of the following countries: Australia, China, Hong Kong, India, Korea, Malaysia, Philippines, Singapore, Taiwan, Thailand, or Vietnam.
- BS/BA degree in Computer Science or relevant technical field with min. 2 years of relevant experience
- Ability to build services on Linux-based systems
- Experience in developing Node.js applications
- Experience in one of the modern frontend frameworks (Vue, React, etc.)
- Experience in web API development (REST, GraphQL, etc.)
- Experience in using SQL and NoSQL database (MySQL, MongoDB, Redis, etc.)
- Experience in AWS, GCP or other cloud computing services
- Familiarity with Git
- Team player and able to work independently
- Proactive, great interpersonal and problem-solving skills
Nice to haves
These aren’t required, but be sure to mention them in your application if you have them.
- Experience in writing TypeScript, Ruby or Python
- Experience in designing and architecting large scale distributed system
- Familiarity with GraphQL
- Familiarity with Socket.IO
- Basic knowledge of machine learning