You design and optimize ClickHouse data infrastructure for billions of events, including table engines, partitioning, materialized views, storage policies, cluster topology, and capacity planning. You improve reliability, observability, schema governance, and query performance while coaching engineers and collaborating with data consumers and the vendor team.
Responsibilities
- Design and optimize the ClickHouse data layer
- Define table engines, partition strategies, materialized views, and storage policies
- Own ClickHouse cluster sizing, topology, and capacity planning
- Develop ClickHouse data reliability and deduplication strategies
- Establish monitoring, alerting, and observability for ClickHouse
- Coach engineers on query optimization and data modeling
- Liaise with the ClickHouse vendor team
- Evaluate ClickHouse features and apply vendor guidance
- Collaborate with analytics, ML, and product consumers
- Improve query performance, schema design, and data formats
- Define and enforce schema versioning and governance standards
Requirements
- BSc in Computer Science
- 5+ years of hands-on software engineering experience with Java, Rust, or Python
- 8+ years of data engineering and data pipeline development experience
- Experience with low-latency real-time systems processing billions of events per day
- Deep hands-on ClickHouse expertise including cluster architecture, table engines, replication, sharding, and query optimization
- Proficiency with Apache Kafka, Spark, Airflow, Kubernetes, Redis, Snowflake, and caching technologies
- Expert-level SQL and query optimization skills
- Experience with Prometheus, Grafana, or similar monitoring and observability tools
- Ability to work independently and proactively drive solutions
- Excellent verbal and written communication skills