About
ClickHouse develops a columnar database and integrations that connect it with data visualization tools, data frameworks, orchestration platforms, and AI tooling. Its technology supports real-time analytics, observability systems, and AI-powered data applications.
Responsibilities
•Own and evolve ClickHouse's Python connector and SDK ecosystem, improving performance, reliability, and API design
•Drive the AI/LLM integration strategy by designing connectors and patterns for RAG architectures, ML feature pipelines, and LLM-powered data applications
•Engage with the open-source community by triaging issues, supporting contributors, advocating for users, and shaping the roadmap based on real-world feedback
•Collaborate with Product, Cloud, and engineering teams to align integration work with platform priorities
•Bring a practitioner's perspective to roadmap decisions, grounding prioritization in Data Engineer and Data Scientist workflows
Requirements
•7+ years of software development experience, including hands-on experience as a Data Scientist or ML Engineer
•Proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform
•Hands-on experience applying AI/ML in production data-engineering contexts, including embedding generation, vector search, feature pipelines, or LLM-powered tooling shipped to production
•Experience with the Python data ecosystem, including Pandas, NumPy, and Pydantic
•Strong database fundamentals, including SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
•Experience with concurrent Python, including threading, multiprocessing, and async patterns
•Strong written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities
Nice to have
•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
•Familiarity with dbt, Airflow, Dagster, or Prefect
Conditions
•Flexible work environment
•Employer contributions toward healthcare
•Stock options for every new team member
•Flexible time off in the US and generous entitlement in other countries
•USD$500 home office setup allowance for remote employees
•Opportunities to engage with colleagues at company-wide offsites
