AvePoint - Senior Splunk Engineer (GIC)

Singapore3w ago

In Office Senior APAC Cloud Computing Nonprofit Senior Data Scientist Solutions Architect Splunk Governance Reporting Terraform Python

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Requirements

• Possess a degree in Computer Science, Engineering, or related discipline. • Minimum 8 years of experience in Infrastructure, Cloud, or Site Reliability Engineering related roles, with at least 5 years of experience specializing in SIEM/Splunk engineering or observability in financial or regulated environments. • Proven hands-on expertise in the following technical areas: • SIEM Platforms: Splunk (must), EL/Elastic • Automation/IaC, Terraform, Ansible, Python, CI/CD tools • Deep understanding of SRE principles, service health modelling, error budgets, and auto-remediation design. • Strong analytical and troubleshooting skills, with the ability to perform deep-dive investigations and develop long-term preventive solutions. • Familiarity with financial sector operational resilience frameworks, regulatory compliance, and incident governance. • Excellent written and verbal communication skills. • Strong interpersonal and communication skills to interact with diverse stakeholders. • Agile, fast learner and able to adapt to changes • Preferred Certifications: • Splunk Certified Power User / Splunk Certified Admin / Splunk Certified Architect • Terraform / Ansible / Python Certified Expert • AWS Certified DevOps Engineer / Azure DevOps Expert • SRE Foundation / Practitioner (DevOps Institute) • ITIL v4 Managing Professional • Any personal data you share with us during the application process will be processed strictly in compliance with applicable data protection laws and our Privacy Notice.

Responsibilities

• Observability Engineering and Governance • Architect and maintain enterprise SIEM solutions aligned with operational resilience mandates (e.g., MAS TRM, DORA, APRA CPS 230). • Lead deployment, configuration, and optimization of Splunk for full-stack visibility across infrastructure, applications, networks, and user experience. • Define and enforce telemetry data governance standards—metrics, logs, and traces—ensuring consistency, retention compliance, and security. • Integrate Splunk with incident management, ITSM, and AIOps systems to enable predictive alerting and anomaly detection. • Act as the SIEM/Splunk subject matter expert (SME) for architecture reviews, platform upgrades, and performance tuning. • Reliability Engineering and Automation • Implement and champion SRE frameworks and reliability practices for mission-critical systems. • Design and automate runbooks, alerts, and self-healing workflows using Python, Ansible, and Terraform. • Collaborate with Application, Infrastructure, and Cyber teams to embed reliability principles into the delivery lifecycle. • Conduct resilience, chaos, and capacity testing aligned with business continuity and disaster recovery standards. • Define and track error budgets, reliability scorecards, and service health indicators for production workloads. • Cloud & Platform Integration • Engineer SIEM for cloud-native workloads in AWS and Azure, ensuring visibility across compute, storage, and network layers. • Integrate Splunk and cloud observability tools into CI/CD pipelines and landing zones to ensure continuous compliance. • Implement infrastructure-as-code (IaC) models using Terraform and Ansible for consistent, auditable provisioning. • Collaborate with Cloud, DevOps, and Security teams to ensure telemetry aligns with audit, compliance, and operational risk requirements. • Operational Excellence and Collaboration • Drive reduction in incident recurrence, MTTR, and manual intervention through observability-led automation. • Partner with Service Delivery, Cyber, and Application teams to enable predictive incident prevention and root cause transparency. • Develop and maintain executive dashboards and reports showcasing availability, reliability KPIs, and operational risk indicators. • Provide technical leadership during major incidents, post-incident reviews, and audits, ensuring lessons learned are codified into automation and process improvements.