7+ years of software development experience, including roles as a Data Engineer, Data Scientist, or ML Engineer.
Deep experience designing and maintaining production-grade Python connectors or SDKs for major platforms.
Hands-on experience with AI/ML applied in data-engineering settings, including embedding generation and vector search.
Strong familiarity with Python libraries like Pandas, NumPy, and Pydantic.
Strong database knowledge, including SQL, data modeling, and query optimization.
Experience with concurrency in Python through threading, multiprocessing, or async patterns.
Excellent communication skills for collaboration across engineering and community engagement.
Responsibilities
Own and enhance ClickHouse's Python connector and SDK ecosystem focusing on performance and API design.
Build and maintain integrations with orchestration and transformation tools to enterprise standards.
Develop AI/LLM integration strategies to position ClickHouse well within modern data architectures.
Engage with the open-source community for feedback, issue triaging, and user advocacy.
Collaborate with cross-functional teams to align integration efforts with platform goals.
Provide a practitioner's viewpoint for roadmap decisions based on real-world Data Engineering and Data Science experiences.
Benefits
Flexible work environment with remote options across multiple countries.
Employer contributions towards healthcare.
Stock options provided for all new hires.
Flexible time off policy, with generous entitlements in various regions.
$500 bonus for home office setup for remote employees.
Opportunities for in-person connections through company-wide gatherings.
Full Job Description
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, the 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'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:
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, 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
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 the 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.
If you have any questions or comments about compensation as a candidate, please get in touch with us at [redacted]. Perks
Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 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 offsites.
