ClickHouse is recognized as one of the most innovative and fast-growing private cloud companies, specializing in real-time analytics and data warehousing. As a Senior Software Engineer, you will be a core contributor to ClickHouse's data engineering ecosystem, building integrations and tools that enhance the performance and usability of the platform for Data Engineers and Data Scientists.
Responsibilities:
- Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
- Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
- Drive the AI/LLM integration strategy: designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
- Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
- Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
- Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows
Requirements:
- 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
- Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
- Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
- Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
- Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
- Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
- Solid experience with concurrent Python: threading, multiprocessing, and async patterns
- Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities
- Experience deploying AI/ML models in production, including inference APIs and vector databases
- Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
- Familiarity with ClickHouse or similar high-performance OLAP platforms
- Familiarity with the JVM ecosystem