Position: Python Serverless Developer
Company: Clicca.agency
Experience required: 5y
Category: Python
English level: upper
Published: 2023-01-01T00:00:00+02:00

Forward Kitchens is the best operating system for ghost kitchens in the US.

**About project:**
Forward Kitchens(https://www.forwardkitchens.com) is the best operating system for ghost kitchens in the US. The food delivery market is booming, and Forward Kitchens will be the technology backbone of the cloud-based kitchens that feed America. As delivery becomes a core business for restaurants worldwide, Forward Kitchens will be the technology platform to help kitchen operators adapt to and succeed in the digital world. Thousands and thousands of people order from our restaurants, and that number is growing rapidly. We are excited to grow our team around the world with the best and most talented engineers.


**What do we offer:**
-Working directly with the team from Silicon Valley;
-Highly skilled colleagues;
-Flexible working schedule;
-20 working days vacation annually;
-Competitive salary;
-Registration through a European legal entity;


**Requirements:**
— 5+ years of experience in Python-based serverless development;
— Proficient with the following technologies on real projects: AWS Cognito, S3, Lambda, SQS, State Functions, RDS, DynamoDB, CDK, Serverless Framework, EC2;
— Should have experience with Github Actions for CI/CD and infrastructure as code through CDK + Serverless;
— Upper-intermediate English level.

**Will be a plus:**
— Experience seeing a project from end to end;
— Experience with AGILE + SCRUM practices.


**Tasks:**
— Defining order ingestion logic: when a customer placed an order, triggering the proper jobs to begin running + adding the order to the correct queues;
— Handling printing events: product has cloud-enabled thermal printers in all of the restaurants. When certain types of orders are created or when a user requests, we initiate printing of order receipts;
— Weekly data aggregation: we use cloudwatch events to trigger weekly aggregations of restaurant summary stats (ie, how much did they make, how much time does each order take, etc).