Splunk Engineer — Performance, Pipelines & Governance

MACHINE LEARNING TECHNOLOGIES LLC; San Jose (CA); On-site; USD 123,984 - 206,640; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC is seeking an experienced Splunk engineer in San Jose to stabilize, optimize, and improve our Splunk environment. The role focuses on search performance, data reliability, governance, and security-focused data workflows.

This position emphasizes SPL tuning, data pipeline reliability, and detection‑as‑code practices to enhance security analytics. The consultant will improve search speed, ensure real‑time data flows where applicable, and work on knowledge object

Qualifications

• 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.

Responsibilities

• 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.
• 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.
• 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.
• 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.

Skills

Splunk Admin

SPL Tuning

Python

Data Pipelines

Governance

Job description

MACHINE LEARNING TECHNOLOGIES LLC is seeking an experienced Splunk engineer in San Jose to stabilize, optimize, and improve our Splunk environment. The role focuses on search performance, data reliability, governance, and security-focused data workflows.

This position emphasizes SPL tuning, data pipeline reliability, and detection‑as‑code practices to enhance security analytics. The consultant will improve search speed, ensure real‑time data flows where applicable, and work on knowledge object