Senior Software Engineer - Python and Data Ecosystem

ClickHouse ClickHouse · Data AI · Israel +2 · Engineering

Senior Software Engineer to own and evolve ClickHouse's Python connector and SDK ecosystem, focusing on integrations with orchestration platforms, transformation tools, and the AI/LLM ecosystem (RAG, ML feature pipelines, LLM-powered data applications). The role requires hands-on experience as a Data Engineer/Scientist/ML Engineer with Python, data ecosystem tools, and AI/ML in data engineering contexts.

What you'd actually do

  1. Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
  2. Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
  3. 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
  4. Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
  5. Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities

Skills

Required

  • Python
  • Data Ecosystem
  • Python connectors
  • SDKs
  • Integrations
  • Orchestration platforms (Airflow, Dagster, Prefect)
  • Transformation tools (dbt)
  • AI/LLM ecosystem
  • RAG architectures
  • ML feature pipelines
  • LLM-powered data applications
  • Pandas
  • NumPy
  • Pydantic
  • Database fundamentals
  • SQL
  • Data modeling
  • Query optimization
  • OLAP/analytical databases
  • Concurrent Python
  • threading
  • multiprocessing
  • async patterns
  • Written and verbal communication skills

Nice to have

  • Experience deploying AI/ML models in production
  • inference APIs
  • vector databases
  • Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
  • ClickHouse
  • JVM ecosystem

What the JD emphasized

  • 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
  • Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production

Other signals

  • AI-powered workflows
  • vector stores for RAG pipelines
  • backends for LLM-powered agents
  • ML feature stores
  • LLM-powered data applications
  • AI/LLM integration strategy