Splunk Engineer: Performance, Governance & Data Pipelines

Quantum Technologies. LLC; San Jose, Northern (CA, KY); Hybrid; USD 130,000 - 170,000; Full time

Job summary

QUANTUM TECHNOLOGIES LLC is seeking an experienced Splunk engineer to stabilize, optimize, and improve our Splunk environment. The role focuses on search performance, data reliability, usability, and governance to meet security, compliance, and analytics requirements.

The ideal candidate combines deep Splunk expertise with hands-on engineering in search optimization, pipeline reliability, knowledge object hygiene, and security-focused data workflows.

Qualifications

• Strong hands-on Splunk Enterprise/Enterprise Security administration and engineering.
• Expert SPL tuning, indexing strategy, search optimization, and performance troubleshooting.
• Proven 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 and advanced handling.

Responsibilities

• Improve search speed and efficiency across large datasets.
• Tune searches, implement caching, and reduce costly queries.
• Enhance workflows for analysts to reuse results without full re-runs.
• Strengthen Splunk data pipelines and real-time data flows.
• Govern knowledge objects, define lifecycle controls, and align with governance policies.
• Support detection-as-code practices and CI/CD for security workloads.

Skills

Splunk Admin

SPL Tuning

Data Pipelines

Governance

Python Scripting

Job description

QUANTUM TECHNOLOGIES LLC is seeking an experienced Splunk engineer to stabilize, optimize, and improve our Splunk environment. The role focuses on search performance, data reliability, usability, and governance to meet security, compliance, and analytics requirements.

The ideal candidate combines deep Splunk expertise with hands-on engineering in search optimization, pipeline reliability, knowledge object hygiene, and security-focused data workflows.