M01 - Cloud Logging & Data Platform Engineer

We are looking for a Logging & Data Platform Engineer to design, build, and operate the logging and operational data-platform capabilities supporting the future SSOE platform.

You will build the platform that collects, transports, stores, indexes, searches, and serves operational data across MOE's technology environment, spanning on-premise infrastructure, networks, applications, GCC, AWS, Azure, and hybrid environments.

• 
  
• As a Logging & Data Platform Engineer, you will build the shared platform capabilities that enable engineering and operations teams to reliably collect and use operational data at scale.
  
• You will work across logging, telemetry ingestion, data movement, storage, search, retention, and platform integration.
  
• The role requires an engineer who understands both traditional enterprise infrastructure and modern cloud-native architectures and can design solutions that work securely and reliably across environment boundaries.
  
• You will work closely with the Observability Engineer on telemetry requirements and with Data Engineering & Analytics on shared data-platform capabilities and integration patterns.
  

• 
  
• Design, build, and operate logging capabilities across on-premise infrastructure, networks, applications, cloud platforms, and hybrid environments
  
• Collect logs from servers, network devices, applications, containers, databases, security appliances, cloud services, and other infrastructure sources
  
• Build scalable log ingestion, routing, enrichment, storage, indexing, search, and retrieval capabilities
  
• Define structured logging standards, schemas, metadata, tagging, and correlation conventions across services
  
• Design appropriate retention, archival, lifecycle, and deletion policies for different classes of operational data
  
• Support correlation between logs, metrics, events, and traces using common identifiers and telemetry standards
  
• Work with the Observability Engineer to implement platform capabilities supporting end-to-end service observability
  

• 
  
• Design secure and resilient data movement between on-premise environments, GCC, and approved external services
  
• Implement collection and forwarding patterns appropriate to different infrastructure, application, network, and security environments
  
• Design for intermittent connectivity, network constraints, buffering, retry, back‑pressure, and recovery between environments
  
• Build event‑driven and streaming patterns for moving operational data between producers and consumers
  
• Integrate legacy and enterprise systems with modern cloud‑native platform capabilities
  
• Define clear interfaces and integration patterns between logging, observability, data engineering, and application platforms
  

• 
  
• Build shared platform capabilities for ingesting, storing, processing, querying, and serving operational data
  
• Design scalable storage and query architectures appropriate to data volume, access patterns, retention requirements, and cost
  
• Build ingestion, filtering, enrichment, and transformation pipelines for operational data
  
• Provide APIs, query interfaces, or other serving mechanisms for authorised downstream consumers
  
• Support operational datasets consumed by the User Portal, dashboards, reporting, automation, and Data Engineering & Analytics
  
• Define schemas and data contracts for shared platform interfaces
  
• Ensure platform changes remain backwards compatible or are coordinated with downstream consumers
  

• 
  
• Design solutions using cloud-native logging, streaming, storage, search, and data capabilities
  
• Build infrastructure and platform configuration using Infrastructure as Code
  
• Automate build, test, deployment, configuration, and platform changes through CI/CD
  
• Design for scalability, resilience, high availability, recoverability, and operational simplicity
  
• Monitor platform capacity, performance, reliability, and cost
  

• 
  
• Enforce MOE and Government data‑classification requirements
  
• Design secure routing and storage of operational data across security zones and environment boundaries
  
• Apply appropriate encryption, access controls, authentication, and authorisation
  
• Ensure logging pipelines do not unnecessarily expose credentials, secrets, or sensitive information
  
• Implement audit‑t