Senior Staff Engineer, Online Datastores

About the Role

Join our team as a Senior Staff Engineer, Online Datastores to build and operate the next generation of reliable, high-performance datastores, setting global standards for availability, scalability, and real-time analytics.

Responsibilities

• Ensure high reliability, uptime, and query performance for Apache Druid clusters on EC2.
• Lead monitoring, alerting, troubleshooting, and incident response using observability tools such as DataDog and CloudWatch.
• Manage data lifecycle: tiering strategies, retention policies, deep storage (S3), local SSD caches, and Aurora MySQL metadata store.
• Operate and tune Zookeeper clusters while ensuring overall cluster stability, coordination, and service discovery.
• Optimize performance and cost efficiency by right-sizing clusters, scaling instances, and balancing ingestion throughput with query workloads.
• Define and drive standards for online datastore operations, including multi-region deployments, failover strategies, SLA/SLOs, and best practices for real-time analytics workloads.
• Provide technical leadership and mentorship, collaborating with data and product teams to define governance, reliability practices, and long-term strategy across datastores (starting with Druid, and over time MongoDB and Postgres).

Requirements

• Hands-on experience setting up and managing Apache Druid clusters (Broker, Router, Coordinator/Overlord, Historical, Middle Manager) including upgrades, troubleshooting and tuning.
• Deep knowledge of Druid operations: indexing, segment management, data partitioning, tiered storage, and query optimization and cluster right-sizing for performance/cost tradeoffs.
• Proficiency in Java (JDK 8+) and Linux/Unix systems, and scripting/automation (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 the broader data ecosystem: streaming ingestion (Kafka/MSK, Flink CDC), cloud storage (S3) and related data infrastructure.
• Experience establishing and operating to SLAs/SLOs, and defining standards and best practices 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 data, infra, and product teams.
• Business-level fluency to read, write and speak in English.