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.