Senior Kibana/Observability Engineer

Remote from: USA
Salary, yearly, USD: 140,000 - 180,000
Department: Software Engineering
Employment type: Full Time,
Job posted: 22 May 2026
Apply before: 22 Jun 2026
Experience level: Senior
Views / Applies: 49 / 13

About ECS

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AI Summary

This role is for a Senior Kibana/Observability Engineer supporting the U.S. Department of Veterans Affairs in a federal healthcare environment. The engineer will design, deploy, and maintain Elastic Observability solutions across enterprise and cloud environments. Responsibilities include developing Kibana dashboards, configuring alerting, and collaborating with engineering and security teams. The position requires US citizenship and ability to obtain a Tier 5 background investigation. The salary range is $140,000-$180,000 per year.

Job Complexity

Easy Hard

AI Insight The role requires 7+ years of experience, deep expertise in Elastic Stack and observability, and federal security clearance, making it highly specialized and challenging.

Salary Analysis

AI Insight The offered salary range of $140,000-$180,000 is competitive and aligns well with the market median for senior observability engineers, which is around $160,000. The upper end is slightly below the market max of $200,000, but the federal benefits and stability compensate.

Key Skills

Kibana Elasticsearch Observability APM Log Management Metrics Dashboarding Alerting Machine Learning Federal Healthcare

Cover Letter Sample

I am writing to express my strong interest in the Senior Kibana/Observability Engineer position at Everforth ECS Federal. With over 7 years of hands-on experience in designing and deploying Elastic Observability solutions, I am confident in my ability to support the U.S. Department of Veterans Affairs in enhancing enterprise telemetry and monitoring capabilities.

In my previous role, I architected and scaled Elastic environments for high-volume metrics and logs, developed complex Kibana dashboards, and configured advanced alerting with Machine Learning. I have extensive experience instrumenting APM agents across Java, .NET, Node.js, and Python stacks, and collaborating with cross-functional teams to improve observability coverage.

I hold an Elastic Certified Engineer certification and am well-versed in federal security requirements. I am eager to bring my expertise in observability and analytics to support the VA's mission-critical operations.

Thank you for considering my application. I look forward to the opportunity to discuss how my skills align with your needs.

Possible Interview Questions

Can you describe your experience designing and deploying Elastic Observability solutions in a large-scale enterprise environment?

I have over 7 years of experience with the Elastic Stack, including designing clusters for high-volume log and metric ingestion. I've deployed Elasticsearch clusters with multiple nodes, configured index lifecycle management, and built Kibana dashboards for real-time monitoring. For example, at my last job, I scaled an observability platform to handle 10 TB of daily data, reducing mean time to resolution by 30%.

How do you approach configuring alerting rules and using Elastic Machine Learning for anomaly detection?

I start by identifying key metrics and logs that indicate system health. I then create alerting rules based on thresholds and use ML jobs to detect anomalies in time-series data. For instance, I set up an ML job to detect unusual spikes in CPU usage, which helped catch a memory leak early. I also use anomaly scores to suppress false positives.

Explain your experience with Elastic APM and how you have instrumented applications across different stacks.

I have instrumented applications in Java, .NET, Node.js, and Python using Elastic APM agents. I configure the agents to capture distributed traces, and I work with development teams to ensure proper context propagation. I also analyze traces to identify performance bottlenecks, such as slow database queries or high latency in external calls.

Describe a time you collaborated with security teams to normalize telemetry and improve observability coverage.

I worked with the security team to integrate threat intelligence feeds into our observability platform. We normalized log formats from various sources (firewalls, IDS, endpoints) and created dashboards to visualize security events. This improved our ability to detect and respond to incidents, and we reduced alert fatigue by correlating events.

How do you ensure your Kibana dashboards are effective for both technical and executive stakeholders?

For technical users, I create detailed dashboards with raw logs, metrics, and traces, using filters and drill-downs for root-cause analysis. For executives, I build high-level overviews using Canvas workpads that show SLIs, SLOs, and key performance indicators. I also use time comparisons and trend lines to highlight improvements or issues.

Everforth ECS Federal is seeking a Senior Kibana/Observability Engineer to support development and operationalization of enterprise observability, telemetry visualization, operational analytics, and monitoring capabilities within a federal healthcare environment supporting the U.S. Department of Veterans Affairs.

The Senior Kibana/Observability Engineer will act as the principal subject matter expert for designing, deploying, and maintaining the Elastic Observability solution (Logs, Metrics, APM, and Uptime/Synthetics) across Department of Veterans Affairs (VA) enterprise and cloud environments.

Must be a US citizen with ability to obtain and maintain a Tier 5 (T5) background investigation (Public Trust Level 5)

7+ years of experience supporting observability, monitoring, analytics, or dashboard engineering initiatives with hands-on Kibana dashboard and visualization development experience

Design and develop native and complex Kibana dashboards, visualizations, analytics workflows, and operational reporting capabilities

Architect, engineer, and scale Elastic environments specifically tuned for time-series metrics, distributed tracing, and high-volume application logs

Deploy and instrument Elastic APM agents across diverse application stacks (Java, .NET, Node.js, Python) to trace transactions and isolate performance bottlenecks

Configure advanced alerting rules and leverage Elastic Machine Learning (anomaly detection) to identify system degradation before it impacts end-users

Collaborate with engineering and security teams to normalize telemetry and improve observability coverage

Build intuitive, role-specific Kibana dashboards and Canvas workpads that unify logs, metrics, and traces for rapid root-cause analysis by IT operations

Monitor system activity and identify anomalous or suspicious operational trends

Support operational awareness, incident monitoring, and continuous monitoring activities

Develop reporting and visualization strategies supporting executive and operational stakeholders

Support implementation and monitoring of Service Level Indicators (SLIs) and Service Level Objectives (SLOs)

Support training and knowledge transfer for operational stakeholders

Salary Range: $140,000-180,000

General Description of Benefits

Qualifications

7+ years of experience with a Bachelor’s degree in Cybersecurity, Information Technology, Engineering or Computer Science, and/or equivalent experience