Log Data Engineer

Responsibilities:

• Support large hybrid Splunk and Cribl deployments through all lifecycle stages (requirements, design, testing, implementation, operations, and documentation).
• Implement and automate log data pipelines using Python for ingestion into platforms like Splunk and OpenSearch.
• Automate platform management with Ansible or similar tools.
• Troubleshoot issues impacting log data platforms.
• Coordinate with platform users and develop training/documentation materials.
• Support log data platform upgrades, including testing coordination.
• Gather and process data from various sources using scripts, APIs, and SQL.
• Build pipelines for log data engineering and testing.

Experience:

• Troubleshoot complex issues and support technical users.
• Work independently and with minimal guidance.
• Experience with IT Service Management, Incident & Problem management.
• Identify and resolve performance bottlenecks and anomalous behavior.
• Collaborate across teams to influence software design and operations.
• Knowledge of security, performance, and disaster recovery best practices.

Required Technical Expertise:

• 3-5 years managing and configuring Splunk Enterprise/Cloud.
• Proficiency in Cribl.
• Experience with Linux/Windows agents for log data engineering.
• Cloud-based solution development using AWS.
• Data onboarding, configuration, dashboard creation, and extraction in Splunk and Cribl.
• Strong scripting and automation skills (bash, Python, etc.).
• Familiarity with Splunk REST APIs, cloud platforms (prefer AWS), and container technologies.
• Experience with data pipeline orchestration platforms.

Preferred Technical Experience:

• Splunk Certification (Admin or Architect).
• Ansible Tower automation.
• GitLab experience.
• Large platform migration experience.
• AWS OpenSearch and Cribl expertise.
• Familiarity with data streaming technologies (Kafka, Kinesis, Spark Streaming).