• Design and implement lakehouse architecture using open-source technologies • Build and optimize ClickHouse deployments for high-performance analytical workloads • Develop custom data transforms and ETL/ELT pipelines using well-supported open-source tools • Create data models that bridge our Postgres application databases with ClickHouse analytics layer • Partner with product and engineering to define data models that serve both analytical and operational needs • Write specifications before writing code—defining contracts, schemas, and expected behaviors upfront • Use AI-assisted coding tools daily to accelerate development and reduce toil • Establish data quality frameworks and observability across the pipeline • Optimize for performance, cost, and reliability at scale