Splunk Data Ops

Splunk Data Ops is the discipline of designing, building, and maintaining scalable data pipelines that feed log, metric, and event data into Splunk indexers at enterprise scale. It involves configuring universal forwarders on hundreds or thousands of sources, managing indexer clusters, optimizing ingestion throughput, and ensuring data availability and consistency across search heads and distributed environments. Data ops engineers solve operational challenges: handling burst traffic, managing indexer disk capacity, configuring data transformation during ingestion, and monitoring the health of the collection infrastructure itself. Enterprise organizations generate terabytes of operational data daily. Splunk is the market-leading platform for real-time operational analytics, and the ability to architect and run a production Splunk environment is highly valued. Data ops engineers command competitive salaries ($140-200k USD senior) because they prevent data loss, optimize cost-per-GB, and unlock real-time visibility that drives incident response and compliance. This skill sits at the intersection of platform engineering, observability, and data infrastructure—making it a gateway to broader DevOps or data platform careers.