Splunk Developer

Role: Splunk Developer

Model: Hybrid based out of Chicago, IL

Rate: Negotiable

JD:

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

 Key Responsibilities

1.      Data Orchestration: Architect the ingestion of the "Three Pillars" (Metrics, Logs, Traces) using OpenTelemetry (OTel) collectors.

2.      Aggregation Strategy: Develop logic to aggregate high-cardinality data to reduce "noise" while maintaining "signal" for troubleshooting.

3.      Analytical Modeling: Use SPL (Search Processing Language) and SignalFlow to perform pattern analysis, detecting anomalies before they trigger traditional threshold alerts.

4.      Visual Storytelling: 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).

Required  Hands on Technical Skills

1. Telemetry & Data Specialization

·       Logs: Proficiency in "Logging-in-Context." You must be able 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). You should know how to calculate percentiles ($P95, P99$), rates of change, and historical averages.

·       Traces: Deep understanding of Distributed Tracing. You must know how to instrument applications (Java, Python, Go) to capture spans and identify bottlenecks in microservices.

 2.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.

3. Hands on - 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).

4. Preferred Qualifications & Certifications

·       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 currently the most "in-demand" skill for this role.