Cloud Observability Engineer information
See salary details
$23.56 - $29.35
0% of jobs
$29.35 - $35.14
1% of jobs
$35.14 - $40.93
2% of jobs
$40.93 - $46.72
6% of jobs
$46.72 - $52.51
12% of jobs
$53.72 is the 25th percentile. Wages below this are outliers.
$52.51 - $58.30
19% of jobs
The median wage is $61.36 / hr.
$58.30 - $64.10
19% of jobs
$64.10 - $69.89
16% of jobs
$70.02 is the 75th percentile. Wages above this are outliers.
$69.89 - $75.68
12% of jobs
$75.68 - $81.47
7% of jobs
$81.47 - $87.26
6% of jobs
How much do cloud observability engineer jobs pay per hour?
As of Sep 13, 2026, the average hourly pay for cloud observability engineer in the United States is $62.89, according to ZipRecruiter salary data. Most workers in this role earn between $53.61 and $71.63 per hour, depending on experience, location, and employer.
A Cloud Observability Engineer is responsible for ensuring the visibility, monitoring, and performance of cloud-based systems and applications. They implement tools and processes to collect metrics, logs, and traces, allowing organizations to detect issues, optimize resources, and maintain system health. Their role often involves collaborating with development and operations teams to troubleshoot problems and improve the overall reliability of cloud services.
To thrive as a Cloud Observability Engineer, you need a solid background in cloud platforms (such as AWS, Azure, or GCP), monitoring frameworks, and scripting or programming languages, often supported by a degree in computer science or related certifications. Familiarity with observability tools like Datadog, Prometheus, Grafana, and log aggregation systems, as well as CI/CD pipelines, is typically required. Strong problem-solving, analytical thinking, and communication skills help you proactively detect issues and collaborate across teams. These skills and qualities are crucial for maintaining system reliability, optimizing performance, and ensuring rapid incident response in dynamic cloud environments.
Cloud Observability Engineers work closely with both development and operations teams to ensure system reliability and performance. They are often responsible for setting up monitoring tools, defining key performance metrics, and proactively identifying issues before they impact users. Regular collaboration involves participating in incident response, sharing insights from logs and metrics, and providing recommendations for architectural improvements. This cross-functional teamwork helps bridge gaps between software deployment and infrastructure management, fostering a culture of shared responsibility for system health.
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