• Design, implement, and maintain data pipelines to ingest and process OpenShift telemetry (metrics, logs, traces) at scale.
• Stream OpenShift telemetry via Kafka (producers, topics, schemas) and build resilient consumer services for transformation and enrichment.
• Engineer data models and routing for multi-tenant observability; ensure lineage, quality, and SLAs across the stream layer.
• Integrate processed telemetry into Splunk for visualization, dashboards, alerting, and analytics to achieve Observability Level 4 (proactive insights).
• Implement schema management (Avro/Protobuf), governance, and versioning for telemetry events.
• Build automated validation, replay, and backfill mechanisms for data reliability and recovery.
• Instrument services with OpenTelemetry; standardize tracing, metrics, and structured logging across platforms.
• Use LLMs to enhance observability capabilities (e.g., query assistance, anomaly summarization, runbook generation).
• Collaborate with platform, SRE, and application teams to integrate telemetry, alerts, and SLOs.
• Ensure security, compliance, and best practices for data pipelines and observability platforms.
• Document data flows, schemas, dashboards, and operational runbooks.