Splunk Consultant

• Integrate Splunk with AWS cloud services including CloudWatch, S3, EC2, Kinesis and container logs.
• Execute regular component updates and lifecycle management across Indexers, Search Heads and Forwarders.
• Conduct routine platform health checks, indexer cluster maintenance and system performance tuning.
• Onboard new data sources and manage custom parsing configurations
• Automate routine maintenance, reporting and log parsing using Python or Shell scripts alongside Splunk REST APIs.
• Support deployment pipelines to enable seamless infrastructure provisioning with minimal manual intervention.
• Collaborate with stakeholders to optimize search query performance for both ad hoc and scheduled tasks.
• Design intuitive dashboards and telemetry visualizations for operational engineering and business teams.

• Minimum two years of experience administering Splunk in enterprise production environments.
• Official Splunk certification such as Enterprise Certified Admin, Architect, or Core Certified Consultant (preferred)
• Practical experience integrating Splunk with AWS cloud infrastructure and services.
• Strong capabilities in Python or Shell scripting for system automation and REST API integration.
• Deep technical expertise in observability, metrics, and log analytics.
• Hands-on experience with data ingestion, source type management, and custom parsing configurations.
• Solid knowledge of indexer cluster maintenance and search head configuration.

Nice to have skills:

• Experience implementing Model Context Protocol (MCP) solutions.
• Familiarity with AI developer tools such as Claude.
• Development experience using TypeScript.
• Exposure to Infrastructure as Code practices and continuous integration pipelines., Education: Bachelor’’s or Master’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.

GlobalLogic estimates the starting pay range for this role to be performed in Sunnyvale, CA, to be $130,000 to $140,000 and reflects base salary only. This pay range is provided as a good-faith estimate, and the amount offered may be higher or lower. GlobalLogic takes many factors into consideration in making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations.