Senior Software Engineer - Python and Data Ecosystem United States (Remote)
$141k - $208kClickHouse
Senior Software Engineer - Python and Data Ecosystem United States (Remote) About ClickHouse Recognized on the 2025 Forbes Cloud 100 list, ClickHouse 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, ClickHouse 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! The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high‑level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling. Our work directly shapes how companies process massive datasets: real‑time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, AI‑powered data applications redefining how teams work with data. We collaborate closely with the open‑source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience. About the role As a Senior Software Engineer specializing in Python and the Data Ecosystem , you'll be a core contributor owning and evolving critical parts of ClickHouse'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 ClickHouse's speed and scale in the frameworks they already use. 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, but 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. You will 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, 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 the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect) Hands‑on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM‑powered tooling in production, not just experimentation Strong understanding of 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 skills; comfortable collaborating across engineering functions and with open‑source communities Experience deploying AI/ML models in production, including inference APIs and vector databases 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 The typical starting salary for this role in the US is $141,000 - $208,000 USD The typical starting salary for this role in US Premium Markets is $157,000 - $232,000 USD Compensation For roles based in United States , the typical starting salary range for this position is listed above. In certain locations, such as the San Francisco Bay Area and the New York City Metro Area, a premium market range may apply, as listed. These salary ranges reflect what we reasonably and in good faith believe to be the minimum and maximum pay for this role at the time of posting. The actual compensation may be higher or lower than the amounts listed, and the ranges may be subject to future adjustments. An individual’s placement within the range will depend on various factors, including (but not limited to) education, qualifications, certifications, experience, skills, location, performance, and the needs of the business or organization. Flexible work environment – ClickHouse is a globally distributed company and remote‑friendly. We currently operate in 20 countries. Healthcare – Employer contributions towards your healthcare. Equity in the company – Every new team member who joins our company receives stock options. Time off – Flexible time off in the US, generous entitlement in other countries. A $500 Home office setup if you’re a remote employee. Global Gatherings – We believe in the power of in‑person connection and offer opportunities to engage with colleagues at company‑wide off‑sites. Culture - We All Shape It As part of our first 500 employees, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here. Check out our blog posts or follow us on LinkedIn to find out more about what’s happening at ClickHouse. Equal Opportunity & Privacy ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here for our Privacy Statement. #J-18808-Ljbffr
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