Location: Plano,TX, USA
Splunk Engineer with AWS/Machine Learning
Business Justification
Network Automation is re engaging with the Network Core & connectivity organization to bring in logs to an observability platform (i.g. Observe, Splunk, etc).Create dashboard, monitors, and alerts to support the connectivity organization in incident response, awareness, and support incident response process for their non-cloud and SaaS platforms.Network Automation has successfully done this work in the past and are being asked to expand on our past success.Additionally we are partnered with the Client team on leveraging Machine Learning for anomaly detection which has the goal to make alarm creation and tuning a much faster process with less false positives.The NAL labor would support as ICs to ramp up this effort.Impact if not approvedIf the expansion of observability topics, Client capability development, and alarm management is not staffed, Connectivity Teams are left without these alarms, each team in the Connectivity Community would need to go through the same learning curve, would not have a complete view of their network/platform performance, would need to self support alarm changes and updates as the data changes.The lack the Machine Learning processing of historical data leaves the opportunity to make Observability support simpler, faster, and well managed.Required:Observability platform (Splunk or Observe), SQL, Python, OPAL, JSON, understanding of DevOps Topics, strong technical skills, such as proficiency with platform logs, metrics, and event detection. Have knowledge of data warehousing and analytics.Experience with proactive monitoring, leveraging telemetry data to detect anomalies, enable identification potential issues before they impact users, and enable faster incident response.PreferredData Brix and or Spark Cluster, Snowflake, Kafka, Network Engineering topics