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ELK / ESS Engineer

Mclean, VA · On-site

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.

Reflexive Concepts

Experience with Elastic Stack (Elasticsearch, Logstash, and Kibana), including Elastic Application Performance Monitoring (APM) * Installing, updating, and/or maintaining multiple Elastic Stack ...

Deegit Inc

Senior NoSQL Administrator

Provo, UT · On-site

Company Description Deegit Inc. • BS in Computer Science, Information Systems or related technical degree. • 5 or more year's experience with ELK (Elasticsearch, Logstash, Kibana) • 5 or more ...

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How much do logstash jobs pay per hour?

As of Jun 19, 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 are the key skills and qualifications needed to thrive as a Logstash Engineer, and why are they important?

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 is Logstash used for?

Logstash is a data processing pipeline used by data analysts and engineers to collect, parse, and transform log and event data from various sources. It is commonly integrated with Elasticsearch and Kibana as part of the Elastic Stack for real-time data analysis and visualization. Proficiency in scripting and understanding of data formats enhances its effective use in monitoring and troubleshooting systems.

What is Logstash and what is it used for?

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 jobs will still be around in 2050?

Logstash-related roles, such as data engineers and DevOps engineers, are expected to remain in demand due to ongoing needs for data processing, integration, and automation. Skills in data management, scripting, and familiarity with cloud environments will continue to be valuable in the evolving tech landscape. However, rapid technological changes may also lead to new tools and roles emerging over time.

Is Logstash still relevant?

Logstash is a widely used open-source data processing pipeline for collecting, parsing, and transforming logs and event data, often as part of the Elastic Stack. It remains relevant for organizations implementing real-time data analysis, monitoring, and centralized logging, especially when combined with Elasticsearch and Kibana. Knowledge of Logstash, along with related tools like Elasticsearch, is valuable for roles in data engineering and DevOps.

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.

Is elastic fully remote?

Logstash is a tool used in data processing and is often part of roles related to Elasticsearch and the Elastic Stack. Whether a specific Logstash job is fully remote depends on the employer, but many companies in the tech industry offer remote positions for roles involving data engineering, DevOps, and related skills. It is common to find remote opportunities for these positions, especially for candidates with experience in scripting, Linux, and cloud environments.

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
Elasticsearch Administrator CGEMJP00320121

Elasticsearch Administrator CGEMJP00320121

R2 Technologies Corporation

New York, NY • On-site

Full-time

Posted 15 days ago

Job description

Overview:
Elasticsearch Administrator CGEMJP00320121
Location - New York (Hybrid 3 days onsite)
Experience Level: Mid - Level ( 8+)
Job Summary:
We are seeking a skilled and experienced Elasticsearch Administrator to manage, maintain, and optimize our Elasticsearch clusters. The ideal candidate will have a strong background in search technologies, systems administration, and monitoring tools, and will be responsible for ensuring the performance, availability, and security of Elasticsearch deployments.
Key Responsibilities:
• Install, configure, and manage Elasticsearch clusters and nodes.
• Monitor Elasticsearch performance and availability using tools like Kibana, Grafana, or Prometheus.
• Implement security policies including authentication, authorization, TLS, and audit logging.
• Troubleshoot and resolve issues related to cluster health, node communication, and indexing.
Required Skills:
• Strong hands-on experience with Elasticsearch (v7.x and above).
• Experience with Kibana, Beats, and Logstash (ELK stack).
• Proficiency in scripting languages like Bash, Python, or Shell.
• Experience with cloud environments such as AWS, Azure, or GCP.
• Knowledge of containerization (Docker, Kubernetes).
Skills:
Kibana,Elasticsearch (v7.x and above),Logstash (ELK stack,Bash,Python,AWS,Docker

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