Observability Platform Engineer

TechDigital Group; Bellevue (WA); On-site; USD 140,000 - 190,000; Full time

Job summary

A leading technology firm in Bellevue, Washington is seeking a candidate to lead the architecture and implementation of an observability strategy within the SIEM modernization ecosystem. Responsibilities include designing telemetry solutions, developing monitoring dashboards, and integrating various monitoring tools. Candidates with experience in managing data events across platforms are encouraged to apply.

Responsibilities

• Lead the architecture and implementation of a comprehensive observability strategy across the SIEM modernization ecosystem.
• Design and build end-to-end telemetry and traceability for data events.
• Develop and maintain dashboards and alerting mechanisms to detect faults and failures.
• Monitor Blob storage utilization and access patterns to identify issues.
• Integrate monitoring solutions with Grafana, Azure Monitor, and PowerBI.
• Ensure observability tooling for Azure Event Hubs: partition health, consumer group lag, throttling events.
• Integrate monitoring with Grafana, Azure Monitor, and PowerBI for technical, operational, and executive views.
• Collaborate with Security, Platform, and Data Engineering to drive actionable insights.

Job description

Responsibilities

• Lead the architecture and implementation of a comprehensive observability strategy across the entire SIEM modernization ecosystem, spanning data pipeline layers (Cribl, Vector, NiFi), event transport (Event Hubs), intermediate storage (Blob), and multiple downstream platforms (Splunk, Snowflake, ADX, Log Analytics, Anvilogic).
• Design and build end-to-end telemetry and traceability for data events as they move across platforms, enabling real-time visibility into ingestion, transformation, routing, and storage processes.
• Develop and maintain dashboards and alerting mechanisms to detect:
• Faults and failures (e.g., dropped messages, ingestion lags, retry loops)
• Latency or throughput bottlenecks across pipelines
• Schema mismatches or format errors
• Duplicate, delayed, or missing data
• Data quality anomalies at point of ingestion and final storage
• Instrument each pipeline component (e.g., Cribl workers, Vector agents, NiFi processors) with health and performance metrics, using native exporters, APIs, or custom collectors.
• Ensure observability tooling is in place for Azure Event Hubs, including partition health, consumer group lag, and throttling events.
• Monitor Blob storage utilization and access patterns to identify ingest failures, access permission issues, or object lifecycle gaps.
• Implement and enforce correlation IDs or tracing metadata to follow data across systems and detect where in the pipeline an issue originates.
• Integrate monitoring solutions with Grafana, Azure Monitor, and PowerBI to support multiple stakeholder needs (technical, operational, and executive-level views).
• Partner closely with Security Engineering, Platform Engineering, and Data Engineering to ensure observability insights are actionable and result in measurable improvements.