Platform Engineer

Job Profile Summary 

We are seeking an experienced AWS Platform Engineer to join our Data Platforms team, designing, building, and managing secure, automated deployment solutions and cloud-native data environments.

The Platform Engineer will collaborate closely with Data Engineers, Data Scientists, Front-End Engineers, and Designers to deliver robust, scalable, and maintainable data infrastructure. This role will leverage Infrastructure as Code (IaC), Kubernetes, Backstage, and GitHub Actions to automate and streamline deployment workflows, ensuring environments are secure, observable, and consistent.

You'll work across multiple teams — including Insight, Data Lake, and Infrastructure — to deliver a high-performance, compliant, and developer-friendly platform ecosystem that accelerates data-driven innovation.

You will champion DevOps and Platform Engineering best practices, using Backstage to enhance the developer experience (DX) and GitHub Actions to drive automation, self-service, and continuous delivery, ensuring reliability and efficiency are embedded across all delivery processes.

You'll deliver:

• Designing, implementing, and managing secure, automated infrastructure in AWS to support data engineering pipelines and analytical workloads.

• Building cloud-native environments using Terraform, Kubernetes (EKS), and GitOps automation (e.g., ArgoCD, GitHub Actions).

• Developing Backstage scaffolder templates and plugins to enable self-service platform capabilities and streamline developer onboarding.

• Enabling end-to-end automation — from infrastructure provisioning to deployment, monitoring, and teardown — ensuring every step is repeatable, observable, and compliant.

• Managing and optimising multi-tenant Kubernetes clusters, improving reliability, scalability, and workload isolation across multiple teams.

• Collaborating with Data Engineering, Data Science, and Analytics teams to deliver performant, reproducible, and developer-friendly environments.

• Designing IaC modules, Backstage templates, and reusable platform components that align with enterprise standards and support cross-team reuse.

• Driving adoption of best-in-class DevOps and Platform Engineering techniques — researching and piloting emerging technologies such as MCP Servers, Airflow, Grafana Cloud, and Crossplane to keep the platform modern and efficient.

• Championing security, governance, and observability through integrated tooling (CloudWatch, CloudTrail, Prometheus, Grafana, and centralised observability).

What you'll bring:

• Proven experience with AWS cloud data platforms, including EKS, EC2, S3, EMR, Lambda, and VPC design.

• Expertise in Infrastructure as Code (Terraform) and container orchestration (Kubernetes, Docker), with strong automation and templating skills.

• Hands-on experience with CI/CD and GitOps tooling, including GitHub Actions, Jenkins, ArgoCD, or FluxCD.

• Experience designing and supporting data pipeline orchestration (e.g., Airflow, Astronomer) within secure, multi-cloud environments.

• Experience with Backstage, developing scaffolder templates, managing catalog integrations, and improving developer self-service capabilities.

• Programming/scripting proficiency in Python and  Bash, with a focus on automation frameworks and platform tooling.

• Familiarity with modern observability stacks (Grafana, Prometheus, Loki, OpenTelemetry) and centralised logging/search platforms.

• Strong collaboration and communication skills, with the ability to explain technical concepts clearly to non-technical stakeholders.

• Solid understanding of AWS security and networking, including IAM, VPC, Transit Gateway, Route53, CloudWatch, and CloudTrail.

• Experience leading software tool evaluations, POCs, and vendor selections to enhance platform capabilities.

We'd love you to know or learn:

• Experience implementing and automating SaaS integrations and data workflows across internal and third-party systems.

• Exposure to Crossplane for cloud-agnostic resource provisioning and multi-cloud management.

• Familiarity with GitOps practices and managing deployments declaratively through pipelines.

• Interest in AI/ML workflow enablement and MCP Server integrations for data-driven automation.

• Understanding of Platform as a Product, Backstage developer portals, and the developer experience lifecycle.

• Experience with data pipeline orchestration using Apache Airflow or Prefect.

• A passion for continuous learning and staying ahead of modern DevOps, Platform Engineering, and GitOps practices.

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