Senior Software Engineer - Python and Data Ecosystem

About the Role

The role requires a deep understanding of the data engineer and data scientist's workflow, as well as the ability to craft tools that enable these professionals to harness ClickHouse's speed and scale within their existing frameworks. This includes working closely with the open-source community, internal teams, and enterprise users to ensure that ClickHouse integrations set the standard for performance, reliability, and developer experience.

The data ecosystem is rapidly evolving, with databases becoming active participants in AI-powered workflows. The ideal candidate will bring product-level insight into what ClickHouse should build and why, based on firsthand experience in data engineering and science.

What You Will Do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, focusing on performance, reliability, and API design.
• Develop and maintain integrations with orchestration platforms such as Apache Airflow, Dagster, and Prefect.
• Build and maintain integrations with transformation tools like dbt and SQLMesh.
• Collaborate on AI and LLM ecosystem integrations, including LangChain, LlamaIndex, n8n, and broader AI tooling.
• Drive architecture, performance, and feature direction across key Python integrations.
• Ensure ClickHouse's columnar architecture and query performance are leveraged to their full potential in the new landscape of AI and data systems.
• Work closely with the open-source community and enterprise users to gather feedback and guide the development of ClickHouse integrations.
• Contribute to the development of production-ready connectors that make ClickHouse the natural choice for next-generation AI and data systems.
• Participate in code reviews and contribute to the improvement of the overall code quality.
• Collaborate with internal teams to align the Connectors team's work with ClickHouse's broader strategy and goals.

What We Are Looking For

• Strong experience in software development with Python, including proficiency in Python 3.x.
• Deep understanding of data engineering principles and the data scientist's workflow.
• Experience with data frameworks such as Apache Spark, Flink, Kafka Connect, and Fivetran.
• Knowledge of orchestration platforms like Apache Airflow, Dagster, and Prefect.
• Familiarity with AI and LLM ecosystems, including tools like LangChain, LlamaIndex, and n8n.
• Strong background in database engineering, particularly with columnar databases.
• Experience with Agile development methodologies and version control systems like Git.
• Excellent problem-solving skills, with the ability to debug complex issues.
• Strong communication and collaboration skills, with experience working in distributed teams.
• Passion for open-source software and community engagement.

Nice to Have

• Experience with cloud platforms such as AWS, GCP, or Azure.
• Knowledge of containerization using Docker and orchestration with Kubernetes.
• Familiarity with CI/CD pipelines and automated testing frameworks.
• Experience with data visualization tools like Tableau, PowerBI, Superset, or Metabase.
• Participation in open-source projects, particularly those related to data engineering and science.

Benefits and Perks

• Competitive salary and equity package.
• Opportunity to work on cutting-edge technology with a leader in the real-time analytics and data warehousing market.
• Collaborative and dynamic work environment with a team of highly skilled professionals.
• Flexible working hours and remote work options.
• Professional development opportunities, including conferences, training, and workshops.
• Access to the latest tools and technologies in the field of data engineering and science.
• Recognized and valued contributions to open-source projects and the broader data community.
• Comprehensive health insurance and wellness programs.
• Generous parental leave policy and family support.
• Annual stipend for professional development and education.

• Highlight Your Python Skills: Ensure your proficiency in Python is clearly demonstrated in your resume and during interviews.
• Showcase Data Engineering Experience: Provide specific examples of your experience in data engineering, including any work with data frameworks or databases.
• Prepare to Discuss AI and Data Trends: Be ready to discuss the latest trends and technologies in AI and data science, and how you see ClickHouse fitting into these landscapes.
• Review ClickHouse's Open-Source Projects: Familiarize yourself with ClickHouse's contributions to open-source projects and be prepared to discuss your potential contributions.
• Emphasize Collaboration and Communication: Highlight your ability to work effectively in distributed teams and communicate complex technical ideas to both technical and non-technical stakeholders.
• Be Prepared to Share Your Portfolio: Come prepared to share examples of your work, such as GitHub repositories or personal projects, that demonstrate your skills and experience.
• Ask About Growth Opportunities: During the interview, ask about opportunities for professional growth and development within the company to show your interest in a long-term career with ClickHouse.