• Design and scale Elasticsearch clusters for ADAS data (camera/radar/lidar logs, events, metadata).
• Build robust indexing pipelines for high volume vehicle telemetry and perception outputs.
• Optimize search queries, mappings, analyzers, sharding, and storage for low-latency retrieval.
• Develop data ingestion flows using Logstash, Beats, Kafka, Spark, or custom ETL pipelines.
• Implement monitoring, alerting, and performance dashboards (Kibana/Grafana).
• Ensure reliability, HA/DR, and security compliance across clusters.
• Collaborate with ML, data engineering, and ADAS perception teams on data discovery and retrieval needs.
• Partner with System Verification, Perception/ML, and Tools teams to capture search use cases and define query SLAs.
• Support data consumers with dashboards, saved searches, alerts, and APIs; evangelize best practices.
• Mentor engineers on schema design, ES DSL, and performance tuning.