SPLUNK engineering consultant

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

Role Overview
We are seeking an experienced Splunk engineer to help stabilize, optimize, and improve our Splunk environment.This role will support search performance, data reliability, usability, and governance practices to ensure Splunk aligns to our security, compliance, and analytics requirements.The ideal candidate combines deep Splunk platform expertise with hands‑on engineering experience in search optimization, pipeline reliability, knowledge object hygiene, and security‑focused data workflows.
Key Responsibilities
Search & Performance Optimization

• Improve speed and efficiency of searches across large datasets.
• Implement caching, tuning, and search-hygiene practices to reduce redundant or costly searches.
• Enhance workflows so analysts can pivot and reuse results without re-running full searches.

Data Integration & Reliability

• Strengthen stability and reliability of Splunk data pipelines for exports and integrations.
• Support real-time or near-real-time data flows where applicable.
• Improve resiliency of indexing, clustering, and correlation workloads.

Governance & Lifecycle Management

• Review and rationalize existing knowledge objects (saved searches, lookups, dashboards).
• Implement monitoring to track field drift, schema changes, or configuration defects that affect detections.
• Define lightweight governance and lifecycle controls for knowledge objects and detection artifacts.
• Support alignment with broader data governance policies, including access models, retention, and auditability.

Advanced Capabilities & Usability

• Enable notebook‑style investigative analysis for collaboration and reproducibility.
• Assist data transformation and ML/AI‑driven analytics enhancements where practical.
• Provide guidance on detection‑as‑code best practices and CI/CD integration for security detection workloads.

Required Skills & Experience

• Strong hands‑on experience with Splunk Enterprise / Enterprise Security administration and engineering.
• Expert level capability in SPL tuning, indexing strategy, search optimization, and performance troubleshooting.
• Proven experience with data pipeline reliability and ingestion stabilization.
• Familiarity with Splunk governance principles (knowledge object hygiene, schema evolution, retention/access practices).
• Proficiency in Python or scripting for automation and advanced handling.

Preferred Skills

• Experience with security detection engineering or detection‑as‑code frameworks.
• Background in ML/AI features within Splunk or adjacent systems.
• Understanding of compliance frameworks and their implications on Splunk governance.

ETHEREUM TECHNOLOGIES LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. ETHEREUM TECHNOLOGIES LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will ETHEREUM TECHNOLOGIES LLC require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract