Senior Software Engineer - Python and Data Ecosystem

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

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 (orchestration, BI, MLOps, or data transformation)

Hands-on experience applying AI/ML in production data-engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling that shipped and ran in production

Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries

Strong 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; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

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

Experience deploying AI/ML models in production, including inference APIs and vector databases