Job Description

Description GSPANN is hiring an L3 Sumo Logic Engineer to lead advanced observability, security monitoring, and analytics across cloud and hybrid environments. The role involves managing and optimizing the Sumo Logic platform, designing enterprise-scale observability frameworks, and troubleshooting complex incidents.

Role and Responsibilities

  • Manage, configure, and optimize the Sumo Logic platform for enterprise observability and security operations.
  • Design and implement end-to-end observability, distributed tracing, and monitoring for applications and infrastructure.
  • Configure Cloud Security Information and Event Management (Cloud SIEM), User and Entity Behavior Analytics (UEBA), and automation workflows.
  • Troubleshoot complex incidents, resolve issues promptly, and escalate to higher tiers when required.
  • Mentor L1/L2 engineers, providing technical guidance and enforcing best practices.
  • Ensure compliance with regulatory frameworks such as PCI, HIPAA, SOC 2, and ISO 27001.
  • Integrate Sumo Logic with third-party platforms, cloud environments, and enterprise security tools.
  • Lead cross-functional collaboration to design observability and security frameworks that enhance reliability and resilience.

    • Skills and Experience

  • 5+ years of experience in IT operations, Site Reliability Engineering (SRE), or security engineering.
  • 3+ years of hands-on expertise with Sumo Logic, including platform administration.
  • Hold Sumo Logic Certified Architect/Admin credentials.
  • Maintain cloud provider certifications (AWS, Azure, or GCP).
  • Certifications like CISSP or CISM are desirable.
  • Demonstrate proficiency in advanced queries, dashboards, visualizations, and alerting frameworks.
  • Automate workflows using strong scripting skills in Python and Bash.
  • Deep knowledge of cloud platforms (AWS/Azure/GCP) and container orchestration technologies.
  • Troubleshoot incidents at enterprise scale, identifying root causes and driving long-term remediation.
  • Utilize machine-learning-driven analytics to enhance detection and response.
  • Bring exposure to DevSecOps, fostering secure automation across pipelines.
  • Design observability at enterprise scale, spanning logs, metrics, traces, and security events.

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