Database Reliability Engineer/Database Engineer (Rubrik Security Cloud Platform)

About the role

About the Role

We are seeking an experienced Database Reliability Engineer to own the reliability, performance, and scalability of our end-to-end database infrastructure. You will manage both our low-latency transactional engines and our real-time analytical/lakehouse storage systems. You will bridge systems engineering, database internals, and automation to maintain rock-solid data integrity, low query latency, and high availability across the entire data lifecycle.

What you'll do

- Performance & Query Optimization: Diagnose and resolve latency regressions, lock/latch contention, index strategies, and memory/disk bottlenecks across both row-oriented and columnar engines.

- Disaster Recovery & Data Integrity: Ensure strict RTO/RPO adherence, automated backup validation, PITR (point-in-time recovery), and data consistency across transactional and analytical stores.

- Storage Optimization & Compaction: Manage compaction policies, partition strategies, file sizing, and storage tiering to minimize storage costs and read amplification.

- Transactional Reliability & Operations: Manage HA, automated failover, replication topology, and zero-downtime maintenance for production RDBMS clusters.

- Analytical Storage Infrastructure: Maintain, scale, and optimize real-time analytical engines (ClickHouse) and lakehouse formats/engines (Apache Iceberg, BigQuery).

- Infrastructure as Code & Observability: Build declarative automation for cluster provisioning, schema migrations, and metric alerting (Prometheus, PromQL, Grafana)

Experience you'll need

- Database Internals & RDBMS Fundamentals:

- Deep understanding of ACID guarantees, WAL, checkpointing, and recovery mechanics (e.g., ARIES-style recovery).

- Comprehensive grasp of concurrency control, transaction isolation levels, lock protocols (2PL, deadlocks), and MVCC architectures.

- Deep knowledge of storage structures: B+ Trees, LSM-Trees, and columnar storage layouts (e.g., Parquet, ORC, ClickHouse Wide/Compact formats).

- Operational Database Experience:

- 4+ years running production database infrastructure, with deep expertise in [PostgreSQL / MySQL].

- Experience optimizing and managing cost/quotas in Google Cloud BigQuery (partitioning, clustering, reservation slots).

- Experience with OLAP DB like: ClickHouse, BQ

- Systems & Kernel Engineering:

- Strong Linux fundamentals: I/O subsystems, page cache vs. engine buffer pools, disk alignment, asynchronous I/O, and memory management.

- Automation & Software Engineering:

- Using Python or Go for building database automation, operators, and CLI tooling.

- Experience with Infrastructure as Code (Terraform) and container orchestration.

Preferred skills and qualifications

- Hands-on administration and performance tuning of ClickHouse (cluster topologies, ZooKeeper/Keeper coordination, MergeTree engine family, mutations, and compaction).