Arivazhagan Pandiyan
Site Reliability Engineering professional with 11+ years of experience supporting large-scale production environments across financial services and logistics platforms.
About Me
I am a seasoned Site Reliability Engineering Lead / Senior SRE with over 11 years of experience supporting large-scale production environments across financial services and logistics platforms. I specialize in building fault-tolerant, scalable infrastructure and ensuring operational excellence for mission-critical applications.
My expertise spans Microsoft Azure and Google Cloud Platform (GCP), with deep hands-on experience in Kubernetes (GKE) environments and enterprise observability platforms including Datadog (APM, Tracing, DBM, RUM), Splunk, and Dynatrace. I serve as the primary Datadog specialist, managing end-to-end observability pipelines and driving telemetry hygiene through OpenTelemetry adoption.
As an Incident Commander, I lead triage for high-severity outages and drive post-incident root cause analysis (RCA) to ensure continuous improvement. I've successfully reduced alert noise from 40% to 10% by implementing AI-driven alerting, Watchdog anomaly detection, and SLO-aligned monitoring standards based on the “Golden Signals” framework.
I'm proficient in Infrastructure as Code using Terraform and Ansible, with strong scripting skills in Python, PowerShell, and Shell. I hold the Microsoft Certified: Azure Administrator Associate (AZ-104) and Datadog Fundamentalscertifications. I'm passionate about reducing toil through automation, optimizing cloud costs, and mentoring engineering teams on observability best practices.
Technical Proficiency
Certifications
Datadog Fundamentals Certification
Datadog · Verified
Microsoft Certified: Azure Administrator Associate
Microsoft · AZ-104
Cloud & Kubernetes
CI/CD & GitOps
Observability
Automation / IaC
Secrets & Security
SRE Practice
ITSM / Incident
Platforms & Infra
Professional Experience
Site Reliability Engineer
Aug 2025 – PresentIzen Labs (Client: Uber Freight) · Remote
- On-Prem to GCP Migration: Spearheaded the comprehensive migration of monitoring infrastructure from legacy on-premises data centers to Google Cloud Platform (GCP), ensuring zero observability gaps.
- Datadog Observability Transformation: Re-architected the monitoring landscape by migrating legacy ELK stack logs and on-prem metrics into Datadog, centralizing telemetry for high-scale GCP workloads.
- High Availability & Error Budgets: Engineered system reliability to maintain 99.99% availability for mission-critical logistics platforms; managed Error Budgets to balance feature velocity with production stability.
- Infrastructure as Code (IaC): Utilized Terraform to architect and provision multi-region Kubernetes (GKE) clusters, implementing modular code to ensure consistent environment states.
- Chaos Engineering Implementation: Enhanced system resilience by conducting scheduled fault-injection experiments using Chaos Mesh, successfully identifying and mitigating single points of failure.
- Kubernetes Scalability: Optimized application performance via manual and automated scaling (HPA/VPA) of workloads within Kubernetes to handle unpredictable traffic spikes.
- CI/CD Pipeline Management: Orchestrated automated deployment pipelines using Jenkins and GitHub, incorporating automated testing to reduce deployment-related incidents.
- Incident Command & RCA: Acted as Incident Commander for high-severity production outages, coordinating cross-functional teams and utilizing ServiceNow for Root Cause Analysis (RCA).
- Alert Optimization: Leveraged Datadog Watchdog and AI-driven alerting to reduce alert noise from 40% to 10%, focusing the team on actionable events.
Site Reliability Engineering Lead
Aug 2023 – Jul 2024New American Funding
- Strategic Team Leadership: Led a high-performing 15-member SRE team responsible for the 24/7 reliability of enterprise-level financial and mortgage systems.
- Enterprise Monitoring Overhaul: Designed and implemented a comprehensive enterprise monitoring strategy utilizing Azure Monitor and PagerDuty, increasing visibility into legacy applications.
- Service Level Definition: Established robust service level indicators (SLIs) and service level objectives (SLOs) to align IT performance with business expectations.
- Operational Automation: Significantly reduced manual toil by automating repetitive operational tasks and diagnostic workflows using PowerShell and Python scripting.
- Cross-Team Incident Coordination: Managed high-severity production responses, facilitating blameless post-mortems and coordinating long-term stability fixes.
Technology Operations Associate
Oct 2017 – Oct 2022Wells Fargo India Solutions
- Infrastructure Maintenance: Maintained enterprise infrastructure supporting mission-critical banking applications.
- Health Monitoring: Monitored performance across Windows and VMware environments, automating diagnostics with PowerShell.
- Collaboration: Partnered with network and database teams to resolve complex production incidents.
System Administrator
Sep 2015 – Oct 2017NTT DATA
- Server Management: Managed Windows and Linux production servers in a 35-member command center for financial clients.
- Hardware Operations: Resolved hardware issues via iLO, DRAC, and SMH; managed security compliance and tool integration.
Support Engineer
Nov 2014 – Sep 2015Firstsource
- Production Support: Monitored server stability (CPU/Disk/Memory) and managed VSS backups for United Health Care and GHX.
- Technical Support: Resolved infrastructure alerts and handled incident ticketing through Kayako and XSmart-control.
Assistant Engineer
Jun 2013 – Aug 2014Cliptos Technologies
- Systems Deployment: Installed and upgraded healthcare IT systems (Meditos) and managed asset inventory.
- Field Support: Configured engineering software solutions and assisted in resolving escalated technical issues.
Key Projects & Initiatives
On-Prem to GCP Telemetry & Observability Migration
Izen Labs · Client: Uber Freight
Spearheaded comprehensive migration of legacy on-premises logging and monitoring infrastructure to Google Cloud Platform with centralized Datadog telemetry.
- Migrated legacy ELK stack logs and on-prem metrics into Datadog, ensuring zero observability blind spots for high-scale GCP workloads.
- Established OpenTelemetry standard pipelines for distributed tracing across cloud microservices.
- Provisioned repeatable monitoring infrastructure using Terraform IaC modules.
Multi-Region Kubernetes & Chaos Resilience Engineering
Uber Freight Workloads
Architected fault-tolerant multi-region Kubernetes (GKE) clusters with automated scaling and proactive chaos engineering fault-injection tests.
- Provisioned multi-region GKE clusters using modular Terraform code for immutable infrastructure.
- Conducted scheduled fault-injection experiments using Chaos Mesh to uncover and mitigate single points of failure.
- Implemented automated HPA/VPA scaling policies to smoothly absorb unexpected freight traffic surges while maintaining 99.99% availability.
AI-Driven Alert Optimization & AIOps Platform
Production Operations
Engineered an AIOps telemetry framework that reduced on-call alert fatigue by 75% and automated incident triage workflows.
- Leveraged Datadog Watchdog AI anomaly detection and Golden Signals framework to drop alert noise from 40% down to 10%.
- Defined actionable SLIs/SLOs and managed Error Budgets to balance feature release velocity with system stability.
- Integrated automated incident dispatch and root cause analysis (RCA) reporting through ServiceNow and PagerDuty.
Enterprise Azure & Dynatrace Observability Overhaul
New American Funding
Designed and executed end-to-end observability strategy across critical financial and mortgage platforms.
- Configured Dynatrace monitors, Real User Monitoring (RUM), and deep distributed tracing for legacy and modern financial apps.
- Automated diagnostic and remediation runbooks using PowerShell and Python scripts to eliminate repetitive manual toil.
- Led 15-member SRE team through high-severity incident responses and blameless post-mortem reviews.
AI Tooling & Workflow Automation via MCP
SRE Automation Initiative
Built custom Model Context Protocol (MCP) integrations and AI-assisted workflows to accelerate SRE diagnostics and incident resolution.
- Connected developer agents (Claude, Cursor) to internal monitoring telemetry and infrastructure APIs via MCP standards.
- Automated log parsing, anomaly summarization, and routine operational runbooks, reducing MTTR for common incidents.
- Authored custom Python automation utilities for cloud health audits and configuration consistency checks.
Operations & Reliability Analytics Platform
Enterprise Infrastructure & Logistics
Built interactive Power BI and SQL-driven observability analytics dashboards tracking mission-critical operational KPIs and SLA adherence.
- Constructed executive Power BI dashboards visualizing multi-service SLA adherence, MTTA/MTTR metrics, and incident trends.
- Aggregated database and operational telemetry using Datadog DBM, Azure SQL, and ServiceNow APIs.
- Delivered real-time operational insights for both engineering leadership and business operations stakeholders.
Education
Bachelor of Technology (Information Technology)
Sri Venkateshwara College of Engineering, Anna University — Chennai, India
Get in Touch
I'm currently open to new opportunities as a Site Reliability Engineer Lead. Whether you have a question or just want to connect, feel free to reach out!
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