Senior Information Security Engineer – Data

Rubrik Rubrik · Enterprise · Bangalore, India · Information Security

Senior Information Security Engineer role focused on bridging Security Operations and Data Engineering, managing SIEM and contributing to a Security Data Lake. The role involves integrating AI tools and LLMs to automate SecOps tasks like incident investigation and response, leveraging Python and cloud data warehousing (Snowflake, BigQuery, Databricks) in a multi-cloud environment.

What you'd actually do

  1. Handle day-to-day operations of market-leading SIEM platforms (e.g., Splunk, Sentinel, or Chronicle). This includes log ingestion from a variety of sources like Network devices, 3rd party vendor APIs, Cloud Services, Webhooks etc.. parsing/normalisation to a common schema, health monitoring checks, User access management and Cost Monitoring.
  2. Develop and maintain the infrastructure/Platform that moves security telemetry from raw sources into Snowflake, BigQuery, or Databricks. Tune/Optimise Ingestion at Scale for cost efficiency and Enable SOC team and Threat Detection team to leverage the Security Data lake for their Search and Analytics workloads.
  3. Proactively integrate AI tools and LLMs into daily workflows; develop AI agents to automate Tier 1/2 SecOps tasks like Incident Investigation and Response.
  4. Partner with global teams across time zones and manage Stakeholder communication.

Skills

Required

  • 5+ years in Security Ops and Engineering
  • SIEM (Splunk, Microsoft Sentinel, Elastic)
  • SOAR platform (Palo Alto XSOAR, Splunk SOAR)
  • Snowflake, BigQuery, and/or Databricks administration/development
  • Python
  • Shell scripting
  • Cloud Infrastructure (AWS/GCP/Azure)
  • AI tools utilization

Nice to have

  • Exposure to Cloud Logging frameworks
  • Familiarity with container orchestration (Kubernetes/EKS/GKE)
  • Interest/experience in building AI-driven security workflows
  • Knowledge of modern CI/CD patterns and DevOps security integrations
  • Experience with Terraform or other IaC tools
  • building/maintaining data platforms that can manage 50-100 TB/day data
  • Multi-cloud familiarity

What the JD emphasized

  • AI agents
  • AI tools and LLMs
  • Security Data Lake
  • SIEM

Other signals

  • AI agents to automate SecOps tasks
  • integrate AI tools and LLMs into daily workflows
  • Security Data Lake architecture
  • SIEM ecosystem health