Platform Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Platform Engineer (P4) based in United Kingdom.

• Design, build, and maintain scalable cloud environments across AWS and Azure, with a primary focus on AWS.
• Develop and evolve reliable platform infrastructure supporting data science and machine learning workflows, including technologies such as Databricks and Posit.
• Automate development and deployment processes using modern CI/CD and DevOps tooling, including GitHub Actions, Azure DevOps, ArgoCD, and GitLab CI.
• Define and manage Infrastructure as Code using tools such as Terraform and Ansible to ensure infrastructure remains consistent, repeatable, and maintainable.
• Configure, operate, and optimize Kubernetes-based environments and Linux systems.
• Develop automation and operational tooling using Python, Bash, and other appropriate scripting technologies.
• Lead or contribute significantly to the implementation of technical solutions, taking ownership from architecture and design through delivery and ongoing improvement.
• Collaborate with cross-functional teams to understand technical and business requirements and translate them into practical platform solutions.
• Advise clients on cloud architecture, infrastructure design, DevOps practices, security, scalability, and long-term platform strategy.
• Work primarily on one main client project at a time, maintaining deep engagement while supporting occasional context switching when business needs require it.
• Contribute to technical documentation, internal engineering initiatives, reusable practices, and knowledge sharing across the platform team.

• 4+ years of professional experience in cloud engineering, platform engineering, infrastructure engineering, or a closely related discipline.
• Demonstrated experience leading at least one significant technical solution or infrastructure implementation from design through delivery.
• Strong hands-on expertise with AWS, which is required for the role.
• Strong practical knowledge of Kubernetes and Linux systems.
• Experience with Infrastructure as Code, particularly Terraform and Ansible.
• Strong scripting and automation capabilities using Python and Bash.
• Professional experience working with CI/CD pipelines and modern DevOps practices.
• Understanding of cloud-native architecture, automation, scalability, reliability, and infrastructure management.
• Experience supporting data science, machine learning, analytics, or other data-intensive workloads is highly relevant.
• Strong consulting skills, with the ability to understand client objectives, ask the right questions, and recommend solutions tailored to specific technical and business needs.
• Strong communication and collaboration skills, with the ability to work effectively with technical and non-technical stakeholders.
• Fluent English at C1 level or higher, both written and spoken.
• High degree of self-organization and autonomy, with the ability to manage priorities effectively in a fully remote environment.
• A proactive, ownership-oriented approach and genuine interest in continuous technical development.
• Ability to provide a valid government-issued ID or passport as required to complete the hiring process.

• Fully remote position within Europe, with the flexibility to work from your home country.
• Flexible working hours designed to support autonomy, focused work, and effective collaboration across distributed teams and clients.
• Competitive B2B compensation of approximately €2,900–€4,100 per month, depending on experience and impact.
• Meaningful ownership of cloud platforms supporting data science and machine learning workflows in complex and regulated life sciences environments.
• Opportunity to work on substantial client projects, typically with one primary engagement at a time.
• Strong consulting environment with direct exposure to client architecture decisions and long-term technical strategy.
• Transparent career framework with defined opportunities for professional progression.
• Dedicated time and budget for continuous professional development, including certifications, courses, and industry learning.
• Modern engineering equipment, including a MacBook or ThinkPad with Linux.
• Remote-first culture centered on trust, ownership, collaboration, and delivery excellence.
• Opportunity to work alongside experienced specialists across cloud engineering, data science, software development, and related technical disciplines.