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Hireful

London / Global

Cloud Engineer - AWS Python

  • £70,000
  • Remote

Job Summary

Salary Range:
£70,000
Work Settings:
Remote
Apply Now

Job Description

We are looking for a skilled AWS Cloud & Python Engineer to bridge the gap between application development and cloud infrastructure for a technically led & growing UK-based company. You'll own the full lifecycle of data transformation applications, from writing clean, efficient Python code to designing the AWS architecture that runs it, working closely with an established cloud engineering team on scalable, high-performance data solutions. Location: remote (UK) or hybrid from the Southwest based head office (Bristol, Bath, Exeter area) Salary: £70,000 basic plus an extensive benefits package. Office visits roughly every two to three weeks (2 days, probably?) for those based further afield - we can talk about this.

Job title: Cloud Engineer. You are likely to come from a Python Developer background who has gone into AWS Devops, or an AWS DevOps background, with strong coding skill in Python. There is a lot of data in this role too - so potentially a Data Engineer, with strong experience of AWS?

What you'll be doing

Design, build and maintain Python applications for real-time decision making and large-scale data transformation

Provision and scale secure AWS infrastructure using Terraform

Architect cost-efficient, low-latency, high-throughput solutions without compromising reliability

Deploy serverless and containerised workloads across Lambda, ECS, EC2, SQS, S3 and RDS

Build and maintain CI/CD pipelines to automate testing, builds and deployments

Set up monitoring and logging with CloudWatch and AWS X-Ray to keep systems running smoothly

What you need to bring

A strong background combining core Python development with hands-on AWS infrastructure work

Hands-on experience with S3, Lambda, ECS, SQS, RDS and EC2

Proven experience deploying environments with Terraform

Experience with Docker and container orchestration such as ECS

Familiarity with data transformation strategies, high-volume data streams, and solid Git and CI/CD practices (desirable)

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