Our client is looking for a Senior Back End Engineer to join their team in building a cutting edge SaaS platform build out. This role will be focused on backend development in an AWS environment. It will require the ability to design, create, understand and extend server components as necessary. You will be supported by other team members and be encouraged to develop new skills in a friendly, but highly productive, environment.
Their products support the environmental and engineering industries and their users range from civil engineers to landscape architects. You will need to demonstrate the ability to understand the technical nature of their work and how it can be enhanced through software. You will need to be a good communicator with strong written and verbal skills.
Responsibilities include but are not limited to: (List duties or tasks critical to success)
Design and implement complex backend containerised and serverless microservices on AWS while leveraging AWS Lambda and Docker Containers.
Integrate with high scale data solutions such as AWS IoT, Kinesis and Snowflake to create comprehensive and scalable solutions.
Develop testable, readable and effective production quality code.
Provide technical guidance and support to colleagues in the design and implementation of solutions.
Work closely with stakeholders to define best in class solutions.
Work within an Agile Development Team to implement these solutions
Partner with fellow developers to estimate task durations and deliver timely results
Experience with developing SaaS applications in an AWS environment with services such as Aurora, RDS, S3, Fargate, Lambda, EKS (or ECS)
Strong experience using containers on Kubernetes
Minimum 5-7 years’ experience, preferably building back-end data services, APIs or microservices in a large-scale production environment
Experience in developing REST and GraphQL APIs
Experience working in an Agile environment
Understanding of the principles of TDD, CI/CD, DevOps
C++ would be a real bonus
Knowledge of software engineering best practices including unit testing and industry standard design patterns.
Use of source control systems (such as Azure DevOps or GIT)
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