Splunk Observability Engineer

Location: Chicago, IL (onsite)

About the role

Design, implement, and optimize a full-stack observability strategy using the Splunk Observability Cloud (formerly SignalFx) and Splunk Enterprise/Cloud. Ensure that engineering teams have 360-degree visibility into system health, moving the organization from reactive "firefighting" to proactive "pattern-based" incident prevention.

Responsibilities

• Architect the ingestion of the "Three Pillars" (Metrics, Logs, Traces) using OpenTelemetry (OTel) collectors.
• Develop logic to aggregate high-cardinality data to reduce "noise" while maintaining "signal" for troubleshooting.
• Use SPL (Search Processing Language) and SignalFlow to perform pattern analysis, detecting anomalies before they trigger traditional threshold alerts.
• Build executive and technical dashboards that correlate disparate data points (e.g., showing how a spike in 500-errors in Logs relates to a specific span in a Trace).

Requirements

Telemetry & Data Specialization

• Logs: Proficiency in "Logging-in-Context." Ability to link logs directly to trace IDs so developers can jump from a failing trace to the specific line of code in the logs.
• Metrics: Expertise in SignalFlow (Splunk’s background streaming analytics language). Knowledge of calculating percentiles (P95, P99), rates of change, and historical averages.
• Traces: Deep understanding of Distributed Tracing. Ability to instrument applications (Java, Python, Go) to capture spans and identify bottlenecks in microservices.

Pattern Analysis & Aggregation

• Anomaly Detection: Ability to configure Metric Finder and MDetector using standard deviations or "Mean Absolute Deviation" to find outliers.
• Data Scrubbing: Skills in using Splunk Ingest Actions or Edge Processors to filter, mask, or aggregate data at the edge to save on license costs and improve search speed.
• Pattern Discovery: Using Splunk’s machine learning commands (e.g., findkeywords, cluster) to group millions of log events into a few dozen "patterns" for faster root cause analysis.

Dashboards & Visualization

• High-Cardinality Handling: Designing dashboards that don’t "break" when viewing thousands of containers.
• Contextual Drill-downs: Building "Glass Tables" (in ITSI) or Unified Dashboards that allow a user to click a metric and immediately see the associated logs.
• Frameworks: Familiarity with the Dashboard Studio and JSON-based dashboard definitions for version control (GitOps).

Qualifications

• DevOps & IAC skills
• Splunk Cloud Certified Metrics User (focuses on the metrics and alerting side)
• Splunk Core Certified Power User (essential for mastering complex SPL for log analysis)
• OpenTelemetry Expert: Knowledge of the OTel Collector configuration (receivers, processors, exporters) is highly desirable.