Lead cloud engineer

Lead cloud engineer


Remote

About the Role


We are seeking an experienced Lead Cloud Engineer with strong expertise in monitoring, observability, and cloud platform reliability . The ideal candidate will design, implement, and manage end-to-end observability solutions using Datadog, Grafana, and related monitoring stacks . This role will partner closely with DevOps, SRE, Application, and Infrastructure teams to ensure the health, performance, and availability of mission-critical systems across multi-cloud environments.

Key Responsibilities

• Design and Implement Monitoring Solutions:
  Architect and deploy scalable monitoring and observability frameworks using Datadog , Grafana , and Prometheus across AWS, Azure, or GCP environments.
• Build Dashboards & Alerts:
  Develop comprehensive dashboards, alerts, and performance indicators to enable proactive monitoring of applications, microservices, APIs, and infrastructure.
• Integrate Observability Tools:
  Integrate Datadog and Grafana with CI/CD pipelines, logging (ELK/CloudWatch), APM, and tracing systems for unified observability.
• Define KPIs and SLOs:
  Work with application and platform teams to define Service Level Objectives (SLOs) , Service Level Indicators (SLIs) , and error budgets .
• Automation & Infrastructure as Code (IaC):
  Automate provisioning, configuration, and management of monitoring tools using Terraform, CloudFormation, or Ansible.
• Performance Analysis & Incident Management:
  Analyze performance bottlenecks, conduct root cause analysis, and drive post-incident reviews with actionable insights.
• Governance & Best Practices:
  Establish observability standards, documentation, and best practices across development and operations teams.
• Mentoring & Leadership:
  Lead a small team of cloud engineers, providing technical guidance, code reviews, and skill development support.

Required Skills & Experience

• 8+ years of experience in Cloud Engineering , DevOps , or Site Reliability Engineering roles.
• Proven expertise with Datadog (metrics, logs, APM, RUM, synthetic monitoring, custom dashboards, alerting).
• Strong hands-on experience with Grafana , Prometheus , and OpenTelemetry .
• Solid understanding of cloud platforms - AWS, Azure, or GCP (certification preferred).
• Proficiency in Infrastructure as Code (Terraform/CloudFormation) and automation scripting (Python, Bash, PowerShell).
• Experience implementing observability pipelines , log forwarding, and distributed tracing.
• Familiarity with Kubernetes , Docker , and microservices architecture .
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience implementing monitoring for Kubernetes clusters and serverless workloads .
• Knowledge of incident response automation and AIOps capabilities in Datadog.
• Exposure to security monitoring and compliance dashboards .
• AWS Certified DevOps Engineer, Azure DevOps Expert, or Datadog Certified Professional preferred.