Splunk EngineerAdmin

• Support Systems Engineering Lifecycle: Engage in requirements gathering design testing implementation operations and documentation for large hybrid Splunk and Cribl deployments.
• Log Data Pipelines: Implement log data pipelines through automation in Python to ingest logs into platforms like Splunk and Open Search.
• Platform Automation: Automate platform management processes using Ansible or other scripting tools/languages.
• Incident Troubleshooting: Troubleshoot incidents impacting the log data platforms and collaborate with platform users.
• Documentation and Training: Develop training and documentation materials to support the log data platform.
• Platform Upgrades: Support log data platform upgrades coordinating testing of upgrades with users.
• Data Processing: Gather and process raw data from multiple disparate sources using scripts APIs and SQL queries for analysis.
• Log Data Engineering: Build log data pipelines to assist in developing and testing log data engineering solutions.
• User Support: Provide support for technical users and conduct requirements analysis.

• Strong troubleshooting and diagnostic skills for complex issues.
• Experience in supporting technical users and conducting requirements analysis.
• Ability to work independently with minimal oversight.
• Familiarity with IT Service Management Incident & Problem Management.
• Proficient in identifying performance bottlenecks diagnosing anomalous system behavior and resolving root cause issues.
• Effective crossteam collaboration to influence the design operations and deployment of highly available software.
• Knowledge of best practices related to security performance and disaster recovery.

Required Technical Expertise:

• 35 years of experience managing and configuring Splunk Enterprise and/or Splunk Cloud.
• Experience with Linux and Windows agents (Splunk Fluentbit/Fluentd) for log data engineering.
• Proficiency in designing developing and deploying cloudbased solutions using AWS.
• Experience onboarding new data configuring creating dashboards and extracting information via Splunk and Cribl.
• Development of systems for data extraction ingestion and processing of large volumes of data.
• Proficiency in scripting and automation (bash python other programming languages).
• Familiarity with Splunk REST APIs.
• Knowledge of cloud platforms (preferably AWS) and container/orchestration technologies.
• Experience with data pipeline orchestration platforms.

Preferred Technical Experience:

• Splunk Certification (Admin or Architect).
• Experience with Ansible Tower automation.
• Experience using GitLab.
• Experience with large platform migration efforts.
• Experience with AWS OpenSearch.
• Experience with Cribl.
• Familiarity with data streaming technologies such as Kafka Kinesis and Spark Streaming.

Note: This role is unsuited for candidates primarily focused on DevOps/CICD. The ideal candidate will have extensive experience in Splunk and log management particularly within large AWS environments and will be adept at using automation to manage data.