About ClickHouse
Recognized on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads.
The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.
We’re on a mission to transform how companies use data. Come be a part of our journey!
About the role
At ClickHouse, we believe in making product decisions grounded in data, not gut feelings. To support that, we've built a comprehensive internal data warehouse — read more about it on our blog . It powers analytics, forecasting, and decision-making across every team in the company.
Our stack centers on ClickHouse as the core storage and processing engine, complemented by dbt , Airflow , S3 , AWS , Superset , and GitHub Actions . We ingest data from 30+ distinct external sources, process over 2.5 PB of data, and deliver most data marts to business consumers with a 1-hour end-to-end latency - a standard that demands highly optimized, rock-solid transformation pipelines.
We're looking for a Senior Data Engineer to help evolve the DWH platform, push its technical boundaries, and deliver reliable, high-performance data models to business users across the organization.
Key Responsibilities
- DWH Platform Development
- Design and develop reusable Airflow components - operators, connectors, and hooks - along with custom integrations tailored to our data architecture.
- Build reusable dbt macros and abstractions: incremental strategies, ETL building blocks, and generic data quality tests, all optimized for ClickHouse-specific behavior and our data patterns.
- Develop DataOps tooling - CI pipelines, data migration frameworks, and security controls - with a strong focus on reliability, self-service usability, and scale.
- Team contributions
- Conduct thorough code reviews for team members and other team contributors.
- Actively participate in technical and architectural design discussions.
- Drive technical leadership in specific areas of our stack.
- Continuously improve the team's development environment, with a focus on automation - including AI-assisted workflows.
- Contribute to platform stability through proactive troubleshooting and timely incident resolution.
- Data modeling
- Develop, refactor, and optimize business data models in line with our modeling standards and