Senior Engineer – Siem Platform Engineering & Operations

Bank of America Bank of America · Banking · Denver, CO +4

Senior Engineer responsible for engineering, monitoring, and optimizing SIEM platforms (Splunk, Microsoft Sentinel) and associated data pipelines, focusing on data quality, platform resiliency, and analytic reliability within a cybersecurity context. The role involves managing ingestion, normalization, and developing observability dashboards, with a requirement for 6+ years of experience in security operations or SIEM engineering.

What you'd actually do

  1. Engineer, monitor, and maintain the operational health and resiliency of SIEM platforms including Splunk Enterprise/Cloud and Microsoft Sentinel.
  2. Implement SIEM platform resiliency controls including cluster monitoring, ingestion latency tracking, and workload distribution optimizations.
  3. Monitor, maintain, and troubleshoot the data ingestion pipeline including Kafka clusters, Cribl pipelines, Splunk Forwarders, and Sentinel connectors.
  4. Develop dashboards for pipeline throughput, message lag, schema drift, and end-to-end data quality validation.
  5. Manage and enforce data SLIs/SLOs across freshness, completeness, correctness, and availability.

Skills

Required

  • Security Operations
  • SIEM Engineering
  • Detection Engineering
  • Incident Response
  • Splunk Enterprise/Cloud
  • Microsoft Sentinel
  • Kafka
  • Cribl
  • Databricks
  • Hadoop
  • Python
  • SQL
  • Pandas
  • Spark
  • CIM
  • OCSF
  • CEF
  • EDR
  • SIEM
  • SOAR
  • Cybersecurity tools

Nice to have

  • offensive security tooling
  • data science processes
  • statistical methods
  • threat hunting
  • detection engineering
  • Azure
  • AWS
  • M365
  • Splunk KV stores
  • Splunk apps
  • SRE-style observability
  • reliability patterns
  • AI enabled Security Operations technologies

What the JD emphasized

  • 6+ years experience in Security Operations, SIEM Engineering, Detection Engineering, Incident Response, or related enterprise disciplines.
  • Hands-on experience with Splunk Enterprise/Cloud and Microsoft Sentinel in large-scale environments.
  • Experience with Kafka, Cribl, Databricks, Hadoop, Python, SQL, Pandas, Spark, or similar data platforms.
  • Experience mapping log sources into structured models such as CIM, OCSF, CEF.
  • Ability to troubleshoot complex SIEM ingestion, data quality, and infrastructure performance issues.