Platform Engineer - Logging & Data Platform (Public Sector)

1-year contract, renewable
Government project
Hybrid work arrangement

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.

What You Will Be Working On

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.

Key Responsibilities

Logging Platform Engineering

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

Data Collection & Integration

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

Data Platform Engineering

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

Cloud & Platform Engineering

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

Security & Governance

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-trail preservation and appropriate retention controls
Ensure data-residency requirements are considered when routing operational data between on-premise, GCC, cloud, and SaaS environments
Participate in security, architecture, and operational-readiness reviews

Reliability & Operations

Define SLOs and operational health indicators for logging and data-platform services
Build monitoring, alerting, failure detection, retry, and recovery into platform components
Monitor ingestion health, processing latency, data loss, storage utilisation, search performance, and platform availability
Participate in incident investigation, root-cause analysis, and post-incident reviews
Participate in operational support and on-call responsibilities for owned services
Maintain architecture documentation, operational procedures, and runbooks

What We Are Looking For

Experience

Minimum 3–5 years of experience in cloud engineering, platform engineering, DevOps, SRE, logging engineering, data platform engineering, or a related discipline
At least 2 years of hands-on experience building or operating production logging, telemetry, or data-platform capabilities
Demonstrated experience working with AWS and/or Azure cloud-native services
Experience integrating on-premise and cloud environments, or operating systems in a hybrid environment
Experience with production data ingestion, streaming, routing, storage, indexing, or search platforms
Experience implementing Infrastructure as Code and CI/CD for production environments
Experience designing systems for scalability, resilience, security, and operational support

Technical Skills

Cloud: AWS/Azure-native logging, streaming, storage, search and data services
On-Premise: Enterprise servers, networks, applications, databases, virtualised infrastructure, and log sources
Logging & Telemetry: Structured logging, log collection, routing, enrichment, correlation, indexing, search, and retention
Infrastructure as Code: Terraform / OpenTofu, Ansible or equivalent
CI/CD: GitLab CI/CD, SHIP-HATS or equivalent automated deployment practices
Automation: Python, PowerShell, Bash or equivalent scripting and automation
Containers: Docker and containerised/cloud-native workloads

Engineering Practices

Treats infrastructure, platform configuration, logging pipelines, and schemas as version-controlled engineering artefacts
Uses Infrastructure as Code and CI/CD for repeatable and auditable platform changes
Designs systems for failure, retry, buffering, scalability, observability, and recovery
Understands the operational and cost implications of high-volume logging and telemetry
Designs reusable platform capabilities rather than one-off solutions for individual applications
Defines clear schemas, interfaces, and ownership boundaries between producers and consumers
Applies backwards-compatible changes and coordinates changes that may affect downstream systems
Automates repeatable operational processes rather than relying on manual procedures
Balances technical excellence with pragmatic delivery and operational sustainability

Nice To Have

Experience with Singapore Government platforms such as TechPass, SHIP-HATS, SEED, and GCC
AWS or Azure cloud certifications
Experience operating large-scale or high-volume logging platforms
Experience with OpenTelemetry and modern telemetry collection patterns
Experience designing platforms spanning data centres and public cloud environments
Experience with event-driven and streaming architectures
Experience migrating or integrating traditional enterprise logging platforms with cloud-native services

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