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Logstash Jobs (NOW HIRING)

Volto USA

ELK Engineer at Las Vegas, NV

Las Vegas, NV · On-site

Key responsibilities include configuring Logstash for data processing, optimizing Elasticsearch for data storage and retrieval, developing Kibana dashboards for insights, and ensuring the system ...

Tech Tammina LLC

ELK Engineer

Alpharetta, GA · On-site

ELK Engineer (Onsite - Alpharetta, GA) ELK Engineer, Alpharetta, GA Locals, "7+ years of experience with ELK Stack: (Elasticsearch, Logstash, Kibana and beats), Ruby and/or Python, GIT and Unix Shell ...

LiquidKinetics

Elastic Stack Engineer

Reston, VA · On-site

Develop and optimize Logstash pipelines and Beats configurations for efficient data ingestion. * Create and maintain Kibana dashboards, visualizations, and alerts to support operational and security ...

Themesoft, Inc.

Remote_Observability Architect

Chicago, IL · On-site

$66.75 - $87.50/hr

ELK Stack (Elasticsearch, Logstash, Kibana) * Observability & Monitoring Architecture * Performance Tuning & Cluster Design * Infrastructure as Code (Terraform/Ansible) Must-Have Skills ELK Stack

Mondo

Elastic Administrator

Evansville, IN · Remote

$60 - $65/hr

Administer and maintain the full Elastic stack, including Elasticsearch, Logstash, and Kibana, across large multi-node production clusters * Manage core platform components including ILM policies ...

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How much do logstash jobs pay per hour?

As of Aug 25, 2026, the average hourly pay for logstash in the United States is $20.44, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $21.39 per hour, depending on experience, location, and employer.

What is Logstash?

Logstash is an open-source data processing pipeline that ingests, transforms, and forwards data from a variety of sources to a designated destination, such as Elasticsearch. It is often used as part of the Elastic Stack (ELK Stack) to collect logs, parse them, and transport them for analysis and visualization. Logstash supports a wide range of input, filter, and output plugins, making it highly versatile for handling logs, metrics, and other event data. Its ability to process and enrich data in real time makes it popular among organizations for centralized logging and monitoring.

What are the key skills and qualifications needed to thrive as a Logstash engineer?

To thrive as a Logstash Engineer, you need strong experience in data pipeline design, ETL processes, and a good understanding of the ELK Stack, often supported by a background in computer science or IT. Familiarity with Logstash configuration, regex, Elasticsearch, Kibana, and tools like Beats, as well as certifications such as Elastic Certified Engineer, are typically required. Analytical thinking, problem-solving, and effective communication help engineers troubleshoot issues and collaborate with cross-functional teams. These skills ensure reliable data ingestion, transformation, and visualization, which are vital for organizational insights and system monitoring.

What are some common challenges Logstash engineers face when managing large-scale data pipelines?

Logstash engineers working with large-scale data pipelines often encounter challenges such as managing throughput bottlenecks, optimizing pipeline performance, and handling diverse data formats. Ensuring data reliability and minimizing latency can require careful tuning of pipeline configurations and efficient resource allocation. Collaboration with DevOps, data engineering, and security teams is common to ensure seamless data flow and to troubleshoot issues quickly, making strong communication skills and adaptability important for success in this role.

What is the difference between Logstash vs Elasticsearch?

AspectLogstashElasticsearch
Primary FunctionData collection, processing, and transformationData storage, search, and analytics
Work EnvironmentPart of the Elastic Stack, used for log and event data processingDistributed search and analytics engine
Required SkillsData pipeline, scripting, and log managementSearch queries, data indexing, and cluster management

Logstash and Elasticsearch are both key components of the Elastic Stack but serve different purposes. Logstash handles data collection and processing, while Elasticsearch stores and enables fast search and analysis of that data. They are often used together to build comprehensive logging and analytics solutions.

More about Logstash jobs

What job categories do people searching Logstash jobs look for?

The top searched job categories for Logstash jobs are:

Logstash jobs near you
Infographic showing various Logstash job openings in the United States as of August 2026, with employment types broken down into 90% Full Time, 1% Part Time, and 9% Contract. Highlights an 83% Physical, 7% Hybrid, and 10% Remote job distribution, with an average salary of $42,520 per year, or $20.4 per hour.

ELK Stack Engg-Admin, ElasticSearch, Logstash, Kibana, GIT, Shell 12+ Mts Con Alpharetta, GA

ZnA Inc

Alpharetta, GA • On-site

Contractor

Re-posted 29 days ago

Job description

ELK Stack Engg-Admin, ElasticSearch, Logstash, Kibana,  GIT, Shell 12+ Mts Con Alpharetta, GA

JPC - 3520

Level 4: (10+ Yrs of experience) 

Loc: Alpharetta, GA 

Dur: 12+ Months Contract ( Hybrid 3 days a week onsite) 


ELK Stack Engineer Cum Admin, ElasticSearch, Logstash, Kibana, beats, Ruby/Python, GIT, Shell 12+ Mths Cont Alpharetta, GA 

Description:

BUILD, Maintian and optimize the ElasticSearch, Eleastic Clusters from Scratch, upgrade from other version to ElasticSearch, 
ELK Administration, ELK Architecture, UNIX/Shell, GIT, Kafka, Configure Grafana dashboards - Great Comm Skills. 

Qualifications -

7+ years of experience with ELK Stack: ElasticSearch, Logstash, Kibana and beats. Good to have Ruby and/or Python, GIT and Unix Shell scripting knowledge.

Responsibilities include:

1. Build, maintain and optimize Elastic clusters focusing on logging use cases.
2. Implement and manage Index Lifecycle Management (ILM) policies, snapshots and searchable snapshots for efficient data storage.
3. Design and implement Hot-Warm- Cold architecture for scalable and cost-effective data management.
4. Configure index templates to ensure consistency and best practices across all indices.
5. Architect and size Elasticsearch clusters based on business requirements and performance needs.
6. Automate deployment and configuration management using Ansible.
7. Write shell scripts to automate routine task and optimize operations.
8. Utilize GIT for version control and collaborative configuration management.
9. Plan and execute Elastic Stack version upgrades and patching with minimal downtime.
10. Configure Grafana dashboards for monitoring and visualization of Elasticsearch data.
11. Set up and manage alerting systems to monitor cluster health and performance.
12. Integrate Logstash, Kafka and Beats for data ingestion and log forwarding.
13. Troubleshoot, diagnose and resolve issues related to Elasticsearch, Logstash, Kibana and related components.
14. Collaborate with cross functional teams to gather requirements and design elastic stack solution tailored to specific use cases.

Soft Skills -
1. Good verbal and written communication skills.
2. Good analytical and problem-solving skills.
3. Good team player.