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Senior Elastic Stack Data Integration Engineer

Job in Colorado Springs, El Paso County, Colorado, 80509, USA
Listing for: CB5 Solutions LLC
Full Time position
Listed on 2026-06-23
Job specializations:
  • IT/Tech
    Systems Engineer, Data Engineering, Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Senior Elastic Stack Data Integration Engineer

At cb5, we are on a mission to find exceptional talent. Our tight-knit organization is led by five brothers, each technology leaders in their respective technical fields and driven to foster a culture of excellence through solidarity. We are seeking a Senior Elastic Stack Data Integration Engineer to serve as a member of a Service Infrastructure team. This team is on the front lines, shaping the systems that protect us from advanced threats.

We are looking for highly motivated, results-oriented professionals who thrive on solving complex technical challenges in a dynamic environment.

The Senior Elastic Stack Data Integration Engineer supports a DOD/DOW customer and will serve as the primary technical authority for designing, building, and maintaining data ingestion pipelines supporting Elastic SIEM. This role focuses on creating scalable, resilient Logstash architectures; developing advanced pipeline logic; normalizing, enriching, and transforming security telemetry; and ensuring reliable delivery of high-fidelity data to Elasticsearch.

This is a full-time position working onsite at a location in Colorado Springs, CO or Huntsville, AL, requiring less than 10% travel.

Key Responsibilities
  • Architect, build, and maintain Logstash pipelines to ingest and transform logs from diverse systems, including network devices, servers, cloud services, and security platforms.
  • Implement parsing, grok patterns, JSON transformations, conditional routing, enrichment logic, and ECS mapping.
  • Optimize pipeline performance, resiliency, and scalability (e.g., persistent queues, pipeline workers, memory tuning, load balancing).
  • Ensure all ingested data aligns to ECS (Elastic Common Schema) or internal schema requirements.
  • Implement data enrichment workflows (GeoIP, threat intel lookups, metadata injection).
  • Validate data completeness, integrity, and fidelity across ingestion flows.
  • Maintain and optimize Logstash clusters, including version management, scaling, tuning, and high-availability configurations.
  • Manage integrations with Beats, Elastic Agent, Kafka, syslog endpoints, and custom data collectors.
  • Monitor ingestion throughput, latency, and error rates; implement proactive alerting and troubleshooting processes.
  • Create and maintain technical documentation, including pipeline diagrams, data flow maps, runbooks, and schema references.
  • Establish enterprise standards for parsing, enrichment, normalization, and ingestion patterns.
  • Support internal and external audits by documenting data handling flows and pipeline logic.
  • Work closely with SIEM integration engineers to align pipelines with customer environments and logging requirements.
  • Partner with detection engineering teams to ensure data supports analytic coverage and rule development.
  • Collaborate with infrastructure and platform operations for deployment, scaling, and reliability engineering.

The successful candidate will have:

  • Demonstrated ability to work independently, drive pipeline architecture decisions, and mentor junior engineers.
  • Strong documentation, workflow diagramming, and communication skills.
  • Deep command of Logstash architecture, patterns, and performance optimization.
  • Mastery of parsing, enrichment, normalization, and ECS alignment.
  • Strong understanding of network protocols, logging patterns, and telemetry generation from enterprise systems.
  • Advanced troubleshooting skills across data ingestion, pipeline logic, and Elastic Stack processing layers.
  • Capability to design scalable, HA ingestion workflows with clear operational boundaries.
  • Ability to conduct data modeling, schema design, and transformation mapping.
  • Effective at interfacing with multiple teams, gathering requirements, and aligning pipeline designs with SIEM analytics needs.
  • Focused on reliability, maintainability, and observability across all pipeline components.
  • Strong attention to detail and a disciplined approach to documentation, versioning, and configuration management.
Qualifications
  • 5+ years of experience in log ingestion, data engineering, or SIEM pipeline development.
  • 2+ years of experience in a lead or senior role, mentoring and guiding other team members.
  • Must…
Position Requirements
10+ Years work experience
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