Senior Software Engineer, ClickHouse

• 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

Desirable

• As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem
• This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use
• We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference
• You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why
• You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:
• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications
• ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real: building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems
• 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