Leidos is seeking a highly proficient Sr. Splunk Engineer to join our current 10-member Strategy, Architecture & Engineering Enterprise Observability team. The Sr. Splunk Engineer will play an essential role in the lifecycle of our infrastructure and related services, from systems analysis, maintenance activities, architecture expansions, security control implementations, to automation and orchestration.

We have planned significant expansion of the Splunk infrastructure and development of new Splunk services and capabilities over the next few years, and you will be responsible for deploying, managing, and enhancing complex systems within the Splunk Enterprise and Cribl environments to achieve these goals.
 

Our current Leidos Splunk infrastructure is complex and dynamic, including but not limited to the following core components, functionality, and services:

Index volume:  8 TB/day with 600+ usersOn premises physical/Virtual infrastructureMultisite indexer cluster: 60+ nodesMultiple search head clusters: 20+ nodesMultiple deployment servers, standalone instances: 10+ nodesCribl intermediate layer:  30+ nodes processing/reducing syslog data distributed across 3 continents~50k unique hostsMore than 100 ODBC connectionsThousands of: unique sources and sourcetypes, dashboards, saved searches, reports, Lookups files and KVstores200+ apps:  including custom and vendor supportedStandard and custom data modelsHundreds of custom/modular inputsAWS, Azure Cloud integrationsKubernetes fluent bit/Loki integrationsDisaster recovery capabilitiesVarious federal and financial governance requirements

In addition to the maintenance and expansion of the current infrastructure, the Strategy, Architecture & Engineering Enterprise Observability team is aggressively pursuing a two-year plan including development objectives in the following areas:

ITSI: Service deconstruction and System-of-systems frameworksOrchestration and Automation: ServiceNow, other Enterprise management systemsSplunk Interface Development and Integration: Advanced Interface/Dashboard development beyond the standard and familiar Splunk dashboardsMachine Learning:  Proficiency in applying statistical algorithms to large and complex data sets to deliver more sophisticated monitoring and alerting services

If you have extensive experience in developing, maintaining, and enhancing complex Splunk systems like those described above, and are skilled in any of the four specified development objectives, we’d love to hear from you!

Required Qualifications:

Bachelor's degree and 8+ years of IT experience, including 5+ years of recent experience in Splunk Engineering role. Additional years of relevant experience will be considered in lieu of Bachelor's degree.5+ experience developing, maintaining, enhancing, complex Splunk environment and servicesProficiency in maintaining Splunk on Linux infrastructure; including advanced troubleshooting of performance issuesAdept at creating, deploying, maintain custom Apps and Add-ons; configuring, deploying, maintaining Splunk Apps/TAsAdept at configuring and maintaining all core Splunk configuration filesProficiency in onboarding and normalizing dataExperience integrating data into the Splunk Common Information ModelAdept at creating, testing and deploying highly optimized regular expressionsProficiency at creating, deploying, maintaining, troubleshooting all Splunk Knowledge objectsExperience in an object-oriented programming language, preferably Python and JavaScriptUnderstanding of source control tools like git and bitbucketIntermediate understanding and ability to use AWS/Azure technologyUnderstanding of iterative development Agile methodologyWorking knowledge of ITIL Change & Configuration ManagementUS Citizenship is required and able to obtain security clearance

Desired Qualifications:

Understanding of data collection/reduction/shaping tools such as Cribl StreamProficiency in Interface/Dashboard development well beyond the standard and familiar Splunk dashboard interfaces and capabilitiesExperience with the deployment of machine learning statistical models applied to large and complex data setsUnderstanding the importance of data and how to apply data in decision making.Expertise in service decomposition with Splunk ITSIPractical applications of automation to workflows and processes - scripting, low-code / no codeFamiliarity with SQL/ODBC interfacesExperience in other systems and network management/monitoring productsComplete or partial Splunk Admin/Architect and Cribl training

Please note that actual salary will be closer to the middle of the posted pay range.

Original Posting Date:2024-11-15

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:Pay Range $104,650.00 - $189,175.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.