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)
- 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.
- Hands-on administration and performance tuning of ClickHouse (cluster topologies, ZooKeeper/Keeper coordination, MergeTree engine family, mutations, and compaction).
- Experience with change data capture (CDC) pipelines (e.g., Debezium, Kafka) feeding transactional updates into ClickHouse/Iceberg.
- Experience managing lakehouse storage patterns using Apache Iceberg (metadata management, snapshot expiration, file compaction/orphan cleanup).
- Experience with automated schema migration tools (e.g., gh-ost, Liquibase, Bytebase).
- Familiarity with distributed consensus engines ( ClickHouse Keeper,Raft, Paxos).
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