Senior Software Engineer - Python and Data Ecosystem

About Click House

Recognized on the 2025 Forbes Cloud 100 list, Click House is one of the most innovative and fast‑growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, Click House leads the market in real‑time analytics, data warehousing, observability, and AI workloads.

The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla. We’re on a mission to transform how companies use data.

Come be a part of our journey!

As a Senior Software Engineer specializing in Python and the Data Ecosystem
, you’ll be a core contributor owning and evolving critical parts of Click House’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 Click House’s speed and scale in the frameworks they already use.

The Connectors team is the bridge between Click House and the broader data ecosystem. We build and maintain the integrations that make Click House accessible to millions of developers, data practitioners, and AI agents worldwide, from high‑level data visualization plugins (Tableau, Power

BI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

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; 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.

Your job is to make that potential real: building the robust, production‑ready connectors that make Click House the natural choice when data practitioners design their next‑generation AI and data systems.

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 and LLM ecosystem:
  Lang Chain, Llama Index, n8n, and broader AI tooling such as embedding pipelines, retrieval‑augmented generation with Click House as a vector store, ML feature stores, and LLM‑powered data applications.

• Own and evolve Click House’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 meet enterprise‑grade quality standards.
• Drive the AI/LLM integration strategy: designing connectors and patterns that make Click House 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, 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…