QuickOrder is a fast-moving SaaS startup. They have created the world's most innovative Restaurant OS combining point of sale, staff management, online ordering, and table reservation. By utilising guest and operational data they improve restaurant profitability and overall revenue effectively enabling their customers to grow.
QuickOrder believes that a great workplace is a workplace combining skilled colleagues with hard work. Their core philosophy is freedom and responsibility, which they believe make the happiest and highest performing workplace.
As a developer at QuickOrder, you will be part of an Agile organisation. They empower their teams to self-organise and manage their own work. They value innovative thinking and always strive to deliver the best possible experience for their customers. Simply put: QuickOrder loves to build jaw-dropping software, that the market has not seen anything like before.
QuickOrder is moving fast and opening new offices in new countries, therefore you will need to strive under those conditions. New opportunities arise often, and new hires will be made regularly which requires you to be a team player and a good communicator.
What you will do:
- Be in charge of making the best possible solutions to the tasks given.
- Contribute to improve the backend of the most innovative restaurant operating system in the world.
- Be a part of creating a better experiences for the customers when they use the product suite.
The ideal candidate for the position:
- 3+ years of experience with PHP
- Proficient in working with Rest API's
- Proficient in creating comprehensive unit tests
- Great communication and collaboration skill
- Experience with Scrum
- Experience with Laravel framework
- Experience in AWS
QuickOrder is a fast-moving company where people with excellence strives. QuickOrder provides an end-2-end solution for restaurants and cafes consisting of POS, Online ordering, schedule planning and table booking. Everything is interconnected making sure all data is gathered in one big backend, we apply machine learning to the data to make business recommendations on guest experience, staffing, etc.