Our client is a large, mission-driven, nationally recognized organization operating at the intersection of healthcare, technology, and community impact. Their teams build and support platforms that serve millions across clinical care, insurance, research, and digital experience domains. The environment balances stability with innovation, with a strong emphasis on engineering craft, continuous improvement, and building technology that delivers measurable value for patients, members, and internal stakeholders. This role joins a fast-growing Observability Engineering group responsible for advancing enterprise-wide insight, performance visibility, and reliability capabilities. The team is modernizing and expanding how the organization uses Splunk-elevating everything from log analytics to distributed tracing and SIEM tooling, enabling data-driven problem solving at scale. As a Lead Splunk Engineer , you will serve as the team's specialist and key contributor for Splunk architecture, engineering, automation, optimization, and overall platform evolution. You'll collaborate closely with platform, cloud, site reliability, and application engineering teams to improve observability maturity across the enterprise. This is a hands-on role for someone who loves building, tuning, automating, and scaling Splunk in complex environments. WHAT MAKES THIS ROLE DIFFERENT: Expert-level Splunk engineering experience , including: Designing, deploying, and scaling Splunk environments Indexer clustering, search head clustering, forwarder architecture Deep knowledge of data ingestion pipelines, props/transforms, normalization, dashboards, and performance tuning Strong experience troubleshooting ingestion, indexing, search performance, and data model issues Strong experience building automation around Splunk and infrastructure (e.g., Ansible, Chef, Terraform, or similar) Demonstrated ability to write high-quality code for automation, tooling, integrations, and pipelines Experience running and supporting high-availability, distributed systems Comfort working across Linux, networking, storage, and VM/container environments Hands-on experience with public cloud concepts (AWS, Azure, or GCP) as they relate to observability and automation Ability to operate in an Agile environment, communicate technical concepts clearly, and drive continuous improvement Participation in on-call rotations and troubleshooting across multiple environments