Senior Software Engineer - Python and Data Ecosystem

at ClickHouse

📍 United States

USD 141,000-208,000 per year

SENIOR

✅ Remote

Used Tools & Technologies

Machine Learning

Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Software Development @ 7 Python @ 4 SQL @ 3 dbt @ 4 Airflow @ 4 JVM @ 3 MLOps @ 7 Communication @ 4 Dagster @ 4 Data Engineering @ 4 API @ 4 BI @ 7 LLM @ 4 OLAP @ 3 Pandas @ 4 Observability @ 4 AI @ 4 Data Modeling @ 3 ClickHouse @ 4 RAG @ 4

Details

ClickHouse is a fast-growing cloud company focused on real-time analytics, data warehousing, observability, and AI workloads. The Connectors team builds and maintains integrations that make ClickHouse accessible across the broader data ecosystem — from visualization plugins to orchestration platforms, data transformation tools, and AI tooling.

Responsibilities

Own and evolve ClickHouse's Python connector and SDK ecosystem, improving performance, reliability, and API design
Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade standards
Drive AI/LLM integration strategy: design connectors and patterns for RAG architectures, ML feature pipelines, embedding pipelines, vector search, and LLM-powered data applications using ClickHouse as a vector store
Engage with the open-source community: triage issues, support contributors, advocate for users, and shape roadmap based on real-world feedback
Collaborate with Product, Cloud, and other engineering teams to align integration work with platform priorities
Bring practitioner perspective to roadmap decisions grounded in Data Engineer / Data Scientist workflows

Requirements

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

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

Compensation

Typical starting salary (United States): $141,000 - $208,000 USD
Typical starting salary (US Premium Markets, e.g., San Francisco Bay Area, New York City Metro): $157,000 - $232,000 USD

Perks

Flexible work environment; remote-friendly and globally distributed
Employer contributions towards healthcare
Equity (stock options) for new team members
Flexible time off in the US; generous entitlement in other countries
$500 home office setup for remote employees
Global company-wide gatherings / offsites

Equal Opportunity & Privacy

ClickHouse provides equal employment opportunities and prohibits discrimination. See the applicant privacy notice linked in the original posting for details.