Summary
We seek a hands-on technical leader to architect, implement, optimize, and govern enterprise observability across AWS infrastructure, applications, microservices, containers, and hybrid environments. The role owns Datadog and AWS-native monitoring strategy, improves reliability and incident response, automates telemetry deployments, and partners with SRE, DevOps, security, and application teams.
Key Responsibilities
Observability Architecture & Engineering
- Design enterprise monitoring for metrics, logs, traces, events, and service health.
- Standardize dashboards, alerts, service-level indicators (SLIs), service-level objectives (SLOs), and instrumentation across AWS accounts and regions.
- Provide end-to-end visibility for distributed systems, microservices, serverless, and containers.
Datadog Platform Ownership
- Lead Datadog Infrastructure Monitoring, APM, Log Management, RUM, Synthetic Monitoring, service maps, and distributed tracing.
- Build AWS/Kubernetes/database integrations, dashboards, anomaly detection, alert routing, and incident integrations.
- Govern tagging, RBAC, data ingestion, cardinality, retention, and platform cost; automate with Datadog APIs and Terraform.
AWS Cloud Monitoring
- Implement observability for EC2, EBS, Auto Scaling, ECS, EKS, Lambda, RDS/Aurora, DynamoDB, S3, CloudFront, API Gateway, ELB, VPC, Route 53, SQS, SNS, and EventBridge.
- Use CloudWatch metrics/logs/alarms, Application Signals, CloudTrail, AWS Config, and X-Ray where appropriate.
- Architect centralized, multi-account and cross-region AWS monitoring.
SRE, Reliability & Incident Management
- Partner with SRE/DevOps teams to define SLIs, SLOs, error budgets, and actionable alerts.
- Improve MTTD and MTTR through proactive detection, root cause analysis, post-incident reviews, and noise reduction.
- Integrate observability with ServiceNow, PagerDuty, and collaboration platforms.
Automation, Performance & Leadership
- Build monitoring-as-code using Terraform/CloudFormation, Python, Bash, AWS CLI, REST APIs, and CI/CD.
- Optimize telemetry pipelines, sampling, log retention, infrastructure utilization, and observability spend.
- Lead architecture reviews, engineering standards, mentorship, platform roadmaps, and cross-team delivery.
Required Qualifications
- Bachelor’s degree in a technical field or equivalent practical experience.
- 10+ years in systems, infrastructure, or cloud engineering; 5+ years hands-on AWS; 3+ years hands-on Datadog or equivalent observability platform.
- Advanced Datadog skills: infrastructure monitoring, APM, log management, dashboards, alerting, integrations, and tracing.
- Strong AWS knowledge, including CloudWatch, CloudTrail, X-Ray, networking, compute, databases, containers, and serverless.
- Experience with OpenTelemetry, Docker/Kubernetes, ECS/EKS, Terraform or CloudFormation, Python/Bash, APIs, and CI/CD.
- Demonstrated production troubleshooting, incident management, SRE practices, and technical leadership.
Preferred Qualifications
- AWS Solutions Architect – Professional or DevOps Engineer – Professional; relevant Datadog certification.
- Prometheus, Grafana, OpenSearch, Splunk, OpenTelemetry Collector, or Fluent Bit experience.
- Multi-account enterprise AWS architecture; IAM, security, compliance, and data governance.
- AIOps, event correlation, automated remediation, or regulated-industry experience.
Success Measures
- Broader observability coverage and adoption of standardized dashboards and alerts.
- Reduced MTTD, MTTR, false positives, and redundant notifications.
- Higher SLO compliance and automated monitoring deployments.
- Improved Datadog and CloudWatch cost efficiency.
- Assess AWS/Datadog monitoring gaps and establish an enterprise roadmap.
- Standardize tagging, instrumentation, dashboards, alerting, and monitoring-as-code.
- Expand critical workload coverage and deliver measurable reliability and cost improvements.
