Posted on Mar 25, 2021 by FGL Partners
A fast-growing software company focused on smart solutions in Health & Wellness is seeking a DevOps engineer. The companies main mission is to use satellite data and smart diagnostics tools to provide innovative services on mobile devices supporting healthy lifestyle and diseases prevention & treatment.
The company is seeking an experienced DevOps Engineer (Development Operations) to join the team on a permanent basis, providing operational support mainly to the software development teams (Back End and Front End). The DevOps Engineer will be responsible for the administration of the IT cloud infrastructure (mostly Azure-based at the moment), including allocation & optimisation of resources, costing and planning, definition of strategies for improvement and innovation, management of our Internet domains (eg DNS), and supporting the application of data protection regulations.
- Minimum of 3 years working experience in DevOps
- Degree in Computer Science, Engineering or another STEM subject
- Intermediate level experience with Python 3, Docker, Git, Linux Shell Scripting, key command line tools and services, CI/CD pipeline technologies (eg Jenkins, Ansible, Travis, Circle, Azure Pipelines)
- Working knowledge of Azure, Other infrastructure Scripting solutions such as PowerShell, Databases, eg MySQL, Mongo, Elasticsearch
- Significant experience with both Windows and Linux operating system environments
- Excellent teamworking and communication skills
- Process-oriented mindset with great documentation skills
- Eligible to live and work in the UK
- Knowledge on one non-Azure cloud provider (eg AWS, GCP)
- Professional qualification in DevOps (eg BCS, Azure, AWS)
- Working knowledge of Flask or Django web service frameworks
- Ruby, Perl, Java development languages, Apache 2, NGINX, Orchestration services (eg Kubernetes), Big data models and file formats, such as NetCDF4, HDF5, In-memory databases, such as Redis, Python testing tools and frameworks (eg Tox, Pytest, Coverage, Hypothesis), Sphinx or any other Python documentation tools.
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