Data Engineering Tech Lead

Key Responsibilities: • 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. Required Skills: • Hands-on experience building streaming data pipelines with Kafka (producers/consumers, schema registry, Kafka Connect/KSQL/KStream). • Proficiency with OpenShift/Kubernetes telemetry (OpenTelemetry, Prometheus) and CLI tooling. • Experience integrating telemetry into Splunk (HEC, UF, sourcetypes, CIM), building dashboards and alerting. • Strong data engineering skills in Python (or similar) for ETL/ELT, enrichment, and validation. • Knowledge of event schemas (Avro/Protobuf/JSON), contracts, and backward/forward compatibility. • Familiarity with observability standards and practices; ability to drive toward Level 4 maturity (proactive monitoring, automated insights). • Understanding of hybrid cloud and multi-cluster telemetry patterns. • Security and compliance for data pipelines: secret management, RBAC, encryption in transit/at rest. • Good problem-solving skills and ability to work in a collaborative team environment. • Strong communication and documentation skills.