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. What You'll Do 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 About You 7+ years of software development experience, including 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
