Location
London

Hours
Full Time

Salary
Competitive salary

About the Role
Allwyn Lottery Solutions is a global leader in digital lottery and gaming solutions, part of the Allwyn Entertainment Group with a strong presence across Europe. Our mission is to enhance player experiences through cutting-edge technology, driving engagement and maximizing returns for good causes. As a Cloud Platform Engineer within the Business Intelligence & Data team, you will design, build, and operate a modern AWS cloud platform that supports large-scale data processing, machine learning, APIs, and web applications. You will collaborate closely with Data Engineers, Developers, Data Scientists, and Architects to deliver secure, scalable, and automated cloud solutions focused on reliability, performance, and innovation.

This role involves AWS platform engineering, cloud networking, security, automation, serverless architecture, observability, and application platform operations. You will help evolve our cloud-native platform ensuring operational excellence, security, performance, and governance across data services and data-driven products.

Key responsibilities include designing and operating cloud infrastructure for data platforms and AI/ML services, developing reusable infrastructure patterns with Infrastructure as Code, building cloud-native serverless architectures, maintaining secure cloud networking, implementing security controls, managing CI/CD and GitOps workflows, supporting deployment and operation of machine learning services, and driving improvements in automation, reliability, security, and cost efficiency.

Experience
- Minimum 5 years in Platform Engineering, Cloud Engineering, DevOps, Site Reliability Engineering, Data Platform Engineering, or similar roles.
- Strong hands-on experience designing, building, and operating production workloads on AWS, including serverless, event-driven, and containerized architectures.
- Solid understanding of AWS cloud infrastructure, networking, and security including routing, DNS, load balancing, TLS, network segmentation, VPN connectivity, IAM, encryption, secrets management, vulnerability management, perimeter protection, and security monitoring.
- Experience supporting data engineering, analytics, business intelligence, and reporting platforms within AWS.
- Proficiency with Infrastructure as Code tools such as Terraform, OpenTofu, Ansible or similar, and automation using Python and/or Node.js.
- Experience implementing CI/CD pipelines, GitOps workflows, and modern cloud deployment practices.
- Strong knowledge of observability, monitoring, alerting, incident response, and troubleshooting complex infrastructure, networking, security, and deployment issues.

About you
- Strong analytical and problem-solving skills with the ability to diagnose complex technical issues and drive solutions.
- Self-motivated and proactive, comfortable working in a fast-paced, lean environment.
- Systems-thinking mindset with the ability to design and optimize end-to-end platform architectures.
- Strong security awareness and understanding of operational risk, compliance, governance, and engineering best practices.
- Excellent collaboration, communication, and documentation skills.
- Passionate about automation, continuous improvement, engineering excellence, and staying current with emerging cloud, platform engineering, data, and AI technologies.

Qualifications
- Degree in Computer Science, Information Technology, Engineering, or equivalent practical experience.
- Excellent verbal and written communication skills with strong command of the English language.
- Desired: Experience supporting machine learning workloads or MLOps, modern data lake and streaming architectures, AWS cost optimisation and FinOps principles.
- Desired: Experience operating in regulated, security-sensitive, or high-availability environments.
- Desired: Experience with test automation frameworks such as PyTest, UnitTest, Vitest, Jest or similar.
- Desired: AWS certifications in Architecture, DevOps, Security, Networking, Data, or Machine Learning.