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Elk Stack Jobs (NOW HIRING)

Tror AI for everyone

ELK / ESS Engineer

Mclean, VA · On-site

Key feature required include query tuning, indexing strategy, cluster monitoring, and troubleshooting, often using the ELK stack. * Designing, implementing, and managing search and analytics ...

Conch Technologies Inc

Full Stack Developer

Tampa, FL · On-site

Experience with monitoring tools such as Splunk, Datadog, Grafana, or ELK Stack. * Understanding of API Gateway, Service Mesh, OAuth2, JWT, and application security. * AWS or Azure certification is a ...

HHB Systems

ELK Engineer

Springfield, VA · On-site

Strong Linux or ELK stack skills * Strong scripting skills using languages (i.e. Ruby, Python, Bash, Perl, etc.) * Experience collaborating with and/or partnering with infrastructure service ...

No Limit Technology

Site Reliability Engineer

Tampa, FL · On-site

$53.75 - $71.50/hr

\n \n \n \n Looking for an SRE experienced in monitoring and observability using Prometheus, Grafana, ELK Stack, DataDog, and Sentry. You will assist in converting clients off of Datadog to an Otel ...

Hive-X

WI · On-site

$100 - $125/hr

The role involves contributing to a sensitive data intelligence project focused on robust data pipelines and Business Intelligence reporting, utilizing expertise in the ELK stack alongside Linux ...

1 point system

.Net full stack developer

New York, NY · Remote

Experience with CI/CD pipelines using Azure DevOps. * Experience with ELK Stack (Elasticsearch, Logstash, Kibana) for monitoring and logging. * Knowledge of Git, REST APIs, and Microservices ...

Navtech, Inc.

URGENT NEED - ELK Architect - REMOTE

$66.50 - $84.75/hr

Qualifications 7+ years of experience of the ELK Stack: ElasticSearch, Logstash, Kibana. Good to have Ruby and/or Python, GIT and ETL Knowledge Candidate will be responsible for: 1. Maintaining and ...

Virtusa Corporation

AWS DevOps Engineer

Phoenix, AZ · On-site

$52.50 - $71.75/hr

Implement monitoring, alerting, and observability solutions using Prometheus, Grafana, ELK Stack, Splunk, etc. Troubleshoot production issues, perform root cause analysis, and improve system ...

Zortech Solutions

Full Stack Java Developer

Woodbridge, NJ · On-site

$53 - $68.50/hr

... ELK Stack, Splunk, AppDynamics * 3+ years of experience -with Cloud Providers like Openshift (OCP), GCP, Azure -with API integration using Apigee, Rest API, Kafka -with tests frameworks using Jasmine ...

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Elk Stack information

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How much do elk stack jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for elk stack in the United States is $59.26, according to ZipRecruiter salary data. Most workers in this role earn between $49.28 and $68.27 per hour, depending on experience, location, and employer.

What is the ELK Stack?

The ELK Stack is a collection of three open-source tools—Elasticsearch, Logstash, and Kibana—commonly used for searching, analyzing, and visualizing large volumes of log data in real time. Elasticsearch is a powerful search and analytics engine, Logstash is a data processing pipeline that ingests and transforms data, and Kibana provides visualization capabilities on top of the data stored in Elasticsearch. Together, they help organizations monitor applications, troubleshoot issues, and gain insights from their data.

What are the key skills and qualifications needed to thrive as an ELK Stack engineer, and why are they important?

To thrive as an ELK Stack Engineer, you need a solid understanding of Elasticsearch, Logstash, and Kibana, as well as experience with data indexing, search, and visualization, typically supported by a degree in computer science or related field. Familiarity with tools like Beats, scripting languages (such as Python or Bash), and certifications like Elastic Certified Engineer are commonly valuable. Strong problem-solving, analytical thinking, and effective communication skills help you interpret data requirements and collaborate with teams. These competencies are crucial to designing, implementing, and maintaining scalable log management and analytics solutions that support business operations.

What are some typical challenges faced when managing and scaling an ELK Stack deployment in a production environment?

One common challenge is ensuring the ELK Stack remains performant as log volume and query complexity increase, which often requires careful resource planning and tuning of Elasticsearch indices. Another challenge is maintaining data security and compliance, as logs can contain sensitive information that must be protected. Additionally, team members often need to collaborate closely with DevOps, security, and development teams to tailor dashboards and alerts to business needs, which can demand strong communication and coordination skills. Proactive monitoring, regular updates, and automation can help address these challenges and ensure reliable log management.
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Elk Stack jobs near you
Infographic showing various Elk Stack job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 88% Full Time, 5% Part Time, 5% Contract, and 1% Nights. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $123,262 per year, or $59.3 per hour.

ELK / ESS Engineer

Mclean, VA • On-site

Tror AI for everyone
See more jobs at Tror AI for everyoneexternal

Contractor

Re-posted 2 days ago

Job description

Job Role: ELK / ESS Engineer

Job Location: McLean, VA (100% Onsite)

Job Type: Contract

Job Description: -

  • Key feature required include query tuning, indexing strategy, cluster monitoring, and troubleshooting, often using the ELK stack.
  • Designing, implementing, and managing search and analytics solutions using Elasticsearch.
  • Responsibilities may include indexing large datasets, optimizing search queries, maintaining cluster performance, and ensuring data availability.
  • Single person in requirement backlog and direct interaction with client.

Key Responsibilities: -

  • Visualization Creation: Build and assemble interactive panels, charts, maps, and metrics using Kibana Lens to create comprehensive dashboards.
  • Data Analysis & Mapping: Design efficient time-series index mappings and data streams to ensure optimal data storage and retrieval.
  • Query Optimization: Utilize aggregations, date histograms, and filters (KQL) to analyze large datasets and ensure fast dashboard response times.
  • Alerting & Monitoring: Set up threshold-based alerts (Watcher) and monitor system health to provide actionable insights.
  • Dashboard Optimization: Tune dashboard panels for performance, implementing data retention policies (ILM) to maintain efficiency.
  • Cluster Management: Deploy, configure, and maintain Elasticsearch clusters on-premise or in cloud environments (AWS, Azure). [NICE TO HAVE]
  • Performance Optimization: Fine-tune query performance, index management, and shard allocation for large-scale data.  [NICE TO HAVE]
  • Data Integration: Develop pipelines for indexing data from various sources using Logstash or ingestion APIs.
  • Monitoring & Security: Monitor cluster health, maintain security protocols, and ensure data integrity.
  • Troubleshooting: Perform root cause analysis on performance bottlenecks and cluster failures 
    Work with Development Teams: Collaborate with software engineers to implement search features and improve user experiences.
  • Provide Technical Support: Troubleshoot and resolve issues related to Elasticsearch performance, data integrity, and availability.
  • Knowledge of indexing strategies for high-volume data.
  • Experience in designing scalable, secure, and resilient search architectures.
  • Ability to work INDEPENDENTLY in agile teams, collaborating with DevOps and Data Engineers
  • Connect AI assistants, agents & automations to your data w/the first managed MCP platform [NICE TO HAVE]

Technical Skills: -

  • Expertise in ELK Stack: Proficient in Elasticsearch, Logstash, and Kibana.
  • Visualization Experience: Strong experience with Kibana visualization tools (Lens, Maps, Graph).
  • Data Modelling and Knowledge of JSON and REST APIs: Familiarity with JSON data format and RESTful API principles is crucial for interacting with Elasticsearch.
  • Querying: Proficiency in Kibana Query Language (KQL) and Elasticsearch aggregations.
  • Monitoring/Observability: Background in creating operational dashboards for log analysis or metric tracking. 
  • Familiarity with Elasticsearch Ecosystem: Knowledge of related tools like Kibana, Logstash, and Beats enhances the engineer’s ability to deliver complete solutions.
  • Basic Programming Skills: Proficiency in programming languages such as Python, Java, or Go is beneficial for automation and customization tasks.