Senior Splunk Engineer: Performance, Data & Governance

Ethereum Technologies LLC; San Jose (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

ETHEREUM TECHNOLOGIES LLC is seeking an experienced Splunk engineer to stabilize, optimize, and improve our Splunk environment. You will focus on search performance, data reliability, usability, and governance to meet security, compliance, and analytics needs.

This role requires hands-on engineering with a deep Splunk platform expertise. Responsibilities include optimizing searches, strengthening data pipelines, rationalizing knowledge objects, and enabling notebook style investigation and CI/CD

Qualifications

• Strong hands-on Splunk Enterprise administration and engineering.
• Expert SPL tuning, indexing and performance troubleshooting.
• Experience with data pipeline reliability and ingestion stabilization.
• Familiarity with governance principles for knowledge objects, schema evolution, retention and access.
• Proficiency in Python or scripting for automation.

Responsibilities

• Improve search performance and stability across large datasets.
• Optimize data pipelines and real-time/incremental data exports.
• Rationalize knowledge objects (saved searches, dashboards, lookups).
• Establish governance controls for detections and schema changes.
• Collaborate on CI/CD practices for security detections.
• Provide guidance on detection-as-code and reproducible workflows.

Skills

Splunk Enterprise Administration

Splunk Enterprise Security

SPL tuning

Indexing strategy

Data pipeline reliability

Governance of knowledge objects

Python scripting

Tools

Splunk

Job description

ETHEREUM TECHNOLOGIES LLC is seeking an experienced Splunk engineer to stabilize, optimize, and improve our Splunk environment. You will focus on search performance, data reliability, usability, and governance to meet security, compliance, and analytics needs.

This role requires hands-on engineering with a deep Splunk platform expertise. Responsibilities include optimizing searches, strengthening data pipelines, rationalizing knowledge objects, and enabling notebook style investigation and CI/CD