Data Engineer

Splunk ES Engineer / Admin (Data Engineer) Location: San Jose, CA (Hybrid – 3 days per week onsite) Contract Duration: 5 months Hours: Full-time (40 hours/week) Max Rate: $99.13 USD/hour Work Authorization: W2 only – No H-1B or Sub-contracting Role Overview We are seeking an experienced Splunk expert to join on a short-term contract and help stabilize, optimize, and enhance our Splunk environment. The focus will be on performance optimization, data reliability, integrations, usability, and governance — ensuring Splunk effectively supports our security, compliance, and analytics needs. Key Responsibilities Search & Performance Optimization • Enhance search speed and efficiency across large datasets. • Implement caching, tuning, and best practices to minimize redundant or expensive searches. • Improve workflows so analysts can reuse or pivot results efficiently. Data Integration & Reliability • Strengthen the reliability of Splunk data pipelines for exports and integrations. • Support real-time or near-real-time data flows. • Improve stability of indexing, clustering, and correlation searches. Governance & Lifecycle Management • Review and rationalize knowledge objects (saved searches, lookups, dashboards). • Monitor field drift and schema changes impacting detections. • Define governance processes for detection lifecycle, versioning, and validation. • Align Splunk governance with enterprise data policies (access, retention, auditability). Advanced Capabilities & Usability • Enable notebook-style investigation support for collaboration and reproducibility. • Explore inline data transformation and ML/AI-driven capabilities. • Provide guidance on best practices for detection-as-code and CI/CD integrations. Required Skills & Experience • 9–12 years of overall experience. • Strong hands-on experience with Splunk Enterprise / Enterprise Security administration and development. • Expertise in SPL optimization, indexing, and performance tuning. • Experience with data integration and pipeline reliability. • Familiarity with data governance practices (knowledge object hygiene, schema evolution, access & retention policies). • Proficiency in Python or scripting for automation and advanced data handling. Nice-to-Have Skills • Experience in detection engineering and detection-as-code frameworks. • Background in ML/AI capabilities within Splunk or adjacent tools. • Understanding of compliance frameworks and their impact on Splunk governance.