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Position Summary
We are seeking a highly experienced Principal Observability Architect to lead the design, implementation, modernization, and optimization of enterprise-scale observability and analytics platforms. This role will serve as the technical authority for log management, observability engineering, telemetry pipelines, AIOps, security analytics, and data lakehouse architectures leveraging Splunk, Databricks, Cribl, OpenTelemetry, and cloud-native technologies.
The ideal candidate possesses deep expertise in traditional observability platforms (Splunk, Dynatrace, AppDynamics, ServiceNow ITOM) and modern data lakehouse architectures utilizing Databricks, Delta Lake, Unity Catalog, and AI/ML-driven analytics. This individual will drive the strategic transformation from legacy SIEM and observability platforms toward scalable, cloud-native observability data lakes.
Key Responsibilities
Enterprise Architecture & Strategy
Define enterprise observability architecture standards, patterns, and roadmaps.
Lead observability transformation initiatives involving Splunk modernization and Databricks adoption.
Develop reference architectures for telemetry ingestion, storage, analytics, security, and AI-driven operations.
Align observability strategies with business, security, compliance, and operational objectives.
Create executive-level architecture presentations, business cases, and technology roadmaps.
Splunk Platform Leadership
Architect large-scale Splunk Enterprise and Splunk Cloud environments.
Design and optimize:
Indexer clusters
Search head clusters
Forwarder architectures
Deployment servers
Data models
ITSI implementations
Define ingestion, retention, indexing, and data lifecycle strategies.
Lead migration initiatives involving:
Splunk to Databricks
Heavy Forwarders to Cribl
SIEM modernization programs
Optimize SPL searches, data models, summary indexing, and dashboard performance.
Databricks & Lakehouse Architecture
Architect enterprise observability data lake solutions using:
Reduce observability platform costs through modernization initiatives.
Design and implement a scalable observability data lake architecture.
Improve telemetry ingestion performance and reliability.
Enable AI-powered analytics and operational intelligence capabilities.
Establish enterprise governance standards for observability and security telemetry.
Support petabyte-scale observability and security analytics workloads.
Ideal Background
Candidates from organizations utilizing large-scale observability environments such as healthcare, banking, retail, telecommunications, logistics, cloud providers, or managed services organizations are highly desirable. Experience supporting environments generating 100TB+ of telemetry per day and integrating Splunk, Databricks, Cribl, OpenTelemetry, and cloud-native data platforms is strongly preferred.
