10+ years in logging, observability, or SIEM engineering.
5+ years architecting enterprise-scale log/telemetry pipelines.
3+ years hands-on with Cribl Stream and Cribl Edge in production environments.
Proven track record managing pipelines with 5-10+ TB/day data throughput.
Expert-level with Splunk ingestion and management of source types.
Strong Linux and scripting skills (Python/Bash); familiar with automation tools like Ansible/Terraform.
Possession of TS/SCI with CI Polygraph security clearance.
Responsibilities
Lead architecture for Cribl Stream and Edge across diverse data domains.
Design high-throughput pipelines with routing and data transformation.
Optimize system performance and resource distribution.
Engineer secure data flows incorporating various governance controls.
Integrate systems with SIEM and cloud services.
Develop reliability frameworks and health metrics for pipelines.
Mentor engineers and uphold architectural standards.
Benefits
Professional development opportunities and mentorship.
Access to advanced technology and tools.
Collaborative work environment with cross-functional teams.
Career growth potential within a leading tech company.
Full Job Description
REQUIRES AN EXISTING/ACTIVE TS/SCI WITH CI POLYGRAPH - NO REMOTE WORK, MUST WORK ON SITE
Job Description:
We are seeking a highly experienced Cribl Engineer to serve as the principal technical authority for observability pipelines built on Cribl Stream and Cribl Edge. This role is designed for a senior technologist with deep expertise in log/telemetry routing, largescale data engineering, and enterprise-grade observability architectures.
You will shape pipeline strategy, design complex routing and transformation logic, drive platform reliability, mentor senior engineers, and serve as the top technical escalation point for Cribl-related challenges.
What You'll Do
Lead architecture and design for Cribl Stream/Edge across multiple enclaves and data domains.
Build high throughput pipelines (multiTB/day) with advanced routing, filtering, enrichment, and replay workflows.
Optimize system performance, worker topology, CPU/memory distribution, queues, and transport mechanisms.
Engineer secure data flows with masking, tokenization, RBAC, PKI/TLS, and other governance controls.
