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Key Responsibilities and Required Skills for Cloud Monitoring Engineer

💰 $90,000 - $160,000

cloudmonitoringobservabilitydevopssre

🎯 Role Definition

This role requires a Cloud Monitoring Engineer to own the end-to-end observability and monitoring lifecycle for cloud-native services. This role combines systems engineering, software instrumentation, SRE best practices, and cross-team collaboration to ensure high availability, fast incident detection and resolution, and measurable service reliability. The ideal candidate builds scalable monitoring platforms, defines SLIs/SLOs, authors actionable alerts and dashboards, automates telemetry pipelines, and partners with engineering teams to drive reliability improvements.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Junior Site Reliability Engineer (SRE)
  • Cloud/DevOps Engineer with exposure to observability
  • Systems/Platform Engineer with monitoring experience

Advancement To:

  • Senior Cloud Monitoring Engineer / Observability Lead
  • Site Reliability Engineering Manager
  • Platform Reliability or Observability Architect

Lateral Moves:

  • Cloud Infrastructure Engineer
  • Security Monitoring / SIEM Engineer

Core Responsibilities

Primary Functions

  • Design, implement, and maintain a centralized observability platform (metrics, logs, traces) across multi-cloud environments (AWS, GCP, Azure), ensuring scalable indexing, retention, and query performance for production workloads.
  • Architect and operate metric collection pipelines using Prometheus, Prometheus Operator, Pushgateway, and metric federation; create robust service-level dashboards in Grafana or equivalent to visualize latency, error rates, and capacity metrics.
  • Lead instrumentation of applications and microservices using OpenTelemetry, client libraries, and language-specific SDKs to capture consistent distributed traces and contextual metadata for end-to-end request visibility.
  • Build and maintain log aggregation and search solutions (ELK/Elasticsearch, Logstash, Fluentd, Loki, Splunk) with structured logging schemas, parsing rules, and retention policies to support fast troubleshooting and compliance audits.
  • Author, calibrate, and maintain alerting strategies and policies that reduce noise and emphasize actionable alerts — mapping alerts to SLIs/SLOs, defining thresholds, and implementing multi-stage escalation with PagerDuty or Opsgenie.
  • Define, measure, and report SLIs, SLOs, and error budgets for business-critical services; partner with product and engineering teams to translate reliability goals into quantifiable targets and remediation actions.
  • Respond to and lead incident management for production outages: perform incident triage, coordinate cross-functional response, conduct post-incident RCA blameless analyses, and ensure remediation and follow-up actions are tracked to completion.
  • Automate observability platform provisioning and configuration using Infrastructure as Code tools such as Terraform and CloudFormation, including secure credential management and environment drift detection.
  • Integrate monitoring and observability into CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI) to ensure new services and releases are instrumented, smoke-tested, and pre-validated for telemetry before production rollout.
  • Implement service and infrastructure health checks, synthetic monitoring, and uptime probes (HTTP synthetic checks, canaries) to detect regressions and availability issues proactively.
  • Monitor and optimize the cost and performance of telemetry systems (indexing, retention, storage tiering), applying sampling, metric rollups, and intelligent retention to balance observability depth and cloud spend.
  • Develop and maintain runbooks, playbooks, and run-level documentation for common failure modes, automated remediation workflows, and on-call procedures to reduce mean time to repair (MTTR).
  • Implement distributed tracing analysis and root-cause workflows to identify latency hotspots, database contention, and downstream service degradation, producing actionable recommendations to engineering teams.
  • Harden observability pipelines for security and compliance by implementing access controls, encryption in transit and at rest, PII redaction in logs, and audit logging aligned with SOC2/GDPR/PCI requirements.
  • Provide expert-level troubleshooting of Kubernetes (EKS, GKE, AKS) observability, including kube-state metrics, cluster-level resource metrics, node/daemonset instrumentation, and pod-level diagnostics.
  • Build and maintain integrations between monitoring platforms and collaboration/communication tools (Slack, Teams, Jira) to deliver contextual, actionable alerts and automate incident ticket creation and lifecycle management.
  • Establish metrics governance: standardize metric names, labels, naming conventions, and dashboard templates to ensure consistency and enable cross-team metric correlation and benchmarking.
  • Conduct capacity planning and forecasting for compute, storage, and telemetry ingestion rates; coordinate scaling strategies and performance tuning to prevent alert storms and index saturation.
  • Mentor and train engineering teams on best practices for observability, application instrumentation, metric design, tracing, and efficient log usage; drive observability adoption through workshops and office hours.
  • Evaluate new observability vendors, open-source tooling, and managed services (Datadog, New Relic, SignalFx, Honeycomb) and lead proof-of-concepts to select the right stack for organizational needs.
  • Implement automated remediation and self-healing actions where appropriate (auto-scaling, circuit breakers, traffic shifting) using runbook automation tooling or orchestration frameworks to reduce human toil.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.
  • Maintain an internal knowledge base of monitoring patterns, playbooks, and historical incident outcomes to accelerate new-hire ramp and institutional learning.
  • Participate in vendor management activities, including SLA review, cost optimization, and contract renewal planning for monitoring and observability services.
  • Work with security teams to detect anomalous behavior and integrate telemetry into threat detection and SIEM pipelines.
  • Assist product managers with telemetry-driven feature health reports and release readiness dashboards.

Required Skills & Competencies

Hard Skills (Technical)

  • Proven experience with observability stacks: Prometheus, Grafana, OpenTelemetry, and distributed tracing concepts (Jaeger, Zipkin, Honeycomb).
  • Hands-on experience with cloud-native monitoring services: AWS CloudWatch, AWS X-Ray, GCP Cloud Monitoring (Stackdriver), Azure Monitor.
  • Proficiency with log aggregation and search tools: ELK (Elasticsearch, Logstash, Kibana), Fluentd/Fluent Bit, Loki, or Splunk.
  • Strong Kubernetes and container observability skills, including metrics, events, kube-state-metrics, cAdvisor, and DaemonSet deployment for collectors.
  • Infrastructure as Code: advanced Terraform and/or CloudFormation skills for provisioning monitoring infrastructure and access controls.
  • Scripting or programming experience in Python, Go, or Bash for building instrumentation, automation, exporters, and remediation scripts.
  • Experience with APM and SaaS vendors such as Datadog, New Relic, Dynatrace, or SignalFx; ability to evaluate cost/benefit and integrate into existing pipelines.
  • Familiarity with CI/CD integration of telemetry tests and pre-production validation step using Jenkins, GitLab CI, or GitHub Actions.
  • Practical knowledge of system performance, CPU/memory profiling, network latency analysis, and database query tracing to link telemetry to root causes.
  • Alerting and incident management tools: PagerDuty, Opsgenie, VictorOps; experience designing on-call rotation policies and escalation paths.
  • Strong SQL skills and familiarity with time-series query languages (PromQL, InfluxQL, or Elasticsearch queries) for metric and log analysis.
  • Security and compliance awareness: log retention policies, data masking/redaction, IAM roles and least-privilege access for observability tooling.
  • Experience optimizing telemetry costs via sampling, cardinality reduction, metric roll-ups, and tiered storage strategies.
  • Familiarity with monitoring for serverless and managed services (AWS Lambda, Google Cloud Functions) and their telemetry limitations.

Soft Skills

  • Excellent communicator: able to explain technical observability concepts to engineers, product owners, and executive stakeholders.
  • Analytical thinker with strong problem-solving skills and an obsession for reducing MTTR and improving system reliability.
  • Collaborative team player who can lead cross-functional reliability initiatives and influence without direct authority.
  • Comfortable in high-pressure incident scenarios; practiced in calm incident leadership and blameless post-mortems.
  • Proactive learner who keeps up with observability trends, tooling, and best practices and mentors others in the organization.
  • Strong organizational skills with an orientation towards documentation, change control, and process improvement.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Computer Science, Engineering, Information Systems, or related technical field; equivalent professional experience accepted.

Preferred Education:

  • Master’s degree in Computer Science, Software Engineering, or related field; or relevant professional certifications (AWS/GCP/Azure cloud certs, HashiCorp Terraform certs).

Relevant Fields of Study:

  • Computer Science / Software Engineering
  • Information Systems / Cloud Computing
  • Computer Engineering / Systems Engineering
  • Data Engineering / Applied Mathematics (for telemetry analytics)

Experience Requirements

Typical Experience Range: 3–8+ years in cloud infrastructure, monitoring, or SRE-focused roles.

Preferred: 5+ years of hands-on experience building and operating observability platforms for production-scale cloud-native systems, demonstrated incident leadership, and proven capability to design SLIs/SLOs and implement telemetry at scale.

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