Senior Engineer

Bank of America Bank of America · Banking · Jersey City, United States +2

This role focuses on designing, operating, and optimizing a large-scale Splunk environment for a financial institution. It involves managing data ingestion, performance optimization, and ensuring security logging for SOC and threat detection capabilities. The role also emphasizes data engineering for observability and governance, with a strong focus on security use cases and compliance.

What you'd actually do

  1. Architect, operate, and optimize a distributed, large-scale Splunk environment (indexer clusters, search head clusters, cluster masters, deployment servers, IDM, ADFS/SAML integrations)
  2. Collaborate with SOC, Incident Response, and Threat Hunting teams to ensure high-quality security log ingestion
  3. Build and manage ingestion pipelines, parsing, field extractions, CIM compliance, HEC configurations, and forwarder architecture
  4. Establish Splunk development standards, dashboards, and naming conventions
  5. Partner with Engineering, Cloud, SecOps, and App teams to drive company-wide observability maturity

Skills

Required

  • 5+ years experience administering large Splunk Enterprise or Splunk Cloud environments
  • Splunk architecture (indexer clustering, search head clustering)
  • SmartStore / S3-compatible object store design
  • Universal/heavy forwarder architecture
  • Ingest actions, parsing, props/transforms
  • KVStore, RBAC, SAML, encryption
  • Deep experience with security log ingestion and SIEM use cases
  • SPL expertise (Search optimization, Summary indexing / data model acceleration, CIM mapping and field normalization)
  • Linux systems engineering
  • scripting (Python/Bash)
  • automation frameworks (Ansible, Terraform, GitOps preferred)

Nice to have

  • Splunk certifications (Core Consultant, Enterprise Admin, Enterprise Architect, ES Analyst/ES Admin, or equivalent)
  • Enterprise Security (ES)
  • SOAR (Phantom or comparable)
  • AWS/Azure/GCP cloud logging architectures
  • high-throughput message brokers (Kafka/FluentD/Cribl)
  • cybersecurity engineering or threat detection

What the JD emphasized

  • large-scale Splunk Enterprise / Splunk Cloud deployment
  • deep expertise in Splunk architecture
  • large-scale data onboarding
  • performance optimization
  • SmartStore/Indexer Clustering
  • security-focused use cases
  • security log ingestion
  • SIEM use cases
  • company-wide observability maturity