Thinklusive Inc
ELK / ESS Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an ELK / ESS Engineer in McLean, VA, with a contract length of "unknown" and a pay rate of "unknown." Key skills include Elasticsearch, query optimization, data integration, and monitoring. Experience in scalable search architectures and agile teamwork is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
April 24, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
McLean, VA
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🧠 - Skills detailed
#Data Integration #AI (Artificial Intelligence) #Data Engineering #KQL (Kusto Query Language) #Data Storage #Agile #Elasticsearch #Data Integrity #Scala #Monitoring #Visualization #Security #Indexing #Automation #Strategy #DevOps #Logstash #Data Analysis #Storage #Datasets
Role description
Role: ELK / ESS Engineer
Location: McLean, VA- 5 days Onsite
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.
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]
Role: ELK / ESS Engineer
Location: McLean, VA- 5 days Onsite
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.
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]
