Senior Staff Engineer, Online Datastores

Hands-on experience setting up and managing Apache Druid clusters, including upgrades, troubleshooting, and tuning. Deep knowledge of Druid operations: indexing, segment management, data partitioning, tiered storage, and query optimization. Proficiency in Java (JDK 8+) and Linux/Unix systems. Scripting/automation skills (Bash, Python) for deployments, maintenance, and performance tuning. Solid understanding of distributed systems concepts such as replication, failover, consensus protocols (Zookeeper), and multi-region deployment strategies. Familiarity with streaming ingestion (Kafka/MSK, Flink CDC), cloud storage (S3), and related data infrastructure. Experience establishing and operating to SLAs/SLOs, and defining standards for real-time analytics workloads. Experience with observability and incident management: metrics collection, dashboards, and alerting (Datadog, Prometheus, Grafana, Cloudwatch or equivalent). Knowledge of security and governance practices including authentication, role-based access, encryption, and audit logging. Demonstrated technical leadership: mentoring engineers, driving architecture discussions, and collaborating with teams.

Ensure high reliability, uptime, and query performance for Apache Druid clusters on EC2. Lead monitoring, alerting, troubleshooting, and incident response using observability tools. Manage data lifecycle: tiering strategies, retention policies, deep storage, and metadata store. Operate and tune Zookeeper clusters. Optimize performance and cost efficiency by right-sizing clusters and balancing ingestion with query workloads. Define and drive standards for online datastore operations, including multi-region deployments and failover strategies. Provide technical leadership and mentorship, collaborating with teams to define governance and strategy.