About the Role
Lead the development and enhancement of Python connectors and SDKs while building robust integrations with data orchestration and transformation tools. Drive AI and LLM integration strategies, collaborate across teams, and contribute to open-source initiatives with a focus on real-world data workflows and community feedback.
Responsibilities
- Lead the ongoing development and improvement of the Python connector and SDK ecosystem, focusing on performance, stability, and intuitive API design
- Develop and sustain high-quality integrations with data orchestration platforms such as Airflow, Dagster, and Prefect
- Maintain strong integrations with transformation tools including dbt to meet enterprise reliability standards
- Define and implement the strategy for integrating with AI and large language models, particularly in retrieval-augmented generation (RAG) systems
- Design patterns and tools that position the platform effectively within machine learning feature pipelines
- Support the use of the platform in data applications powered by large language models
Requirements
- Experience in designing and maintaining Python-based data connectors or SDKs
- Strong understanding of data orchestration tools such as Airflow, Dagster, or Prefect
- Familiarity with data transformation frameworks like dbt
- Proven ability to build and maintain enterprise-grade software integrations
- Knowledge of AI and machine learning application architectures, including RAG
- Active participation in open-source projects, including issue triage and contributor support
Nice to Have
- Demonstrated contributions to open-source data or infrastructure projects
- Experience working with large-scale data systems in production environments
- Background in shaping product roadmaps based on user feedback and technical insights
- Ability to collaborate effectively with product, cloud, and engineering teams
- Understanding of data engineer and data scientist workflows and pain points
- Experience advocating for developer communities and representing technical platforms
Tech Stack
Python, SQL, Airflow, Dagster, Prefect, dbt, Large Language Models (LLMs), RAG architectures, Machine learning pipelines, Open-source development tools
Benefits
- Competitive compensation and equity package
- Opportunities for professional growth and technical leadership
- Support for open-source contributions and community engagement
- Flexible work environment with remote-friendly policies
- Access to cutting-edge data technologies and AI infrastructure
Compensation
Competitive salary and equity package commensurate with experience
Work Arrangement
Remote-friendly with flexibility for global collaboration
Team
Part of a distributed engineering team focused on developer tools and data ecosystem
Company Culture
- Emphasis on technical excellence and real-world usability
- Strong commitment to open-source principles and community collaboration
- Data-driven decision-making informed by user workflows
- Cross-functional teamwork across product, cloud, and engineering
- Focus on building tools that serve practical data engineering and science needs
Additional Information
- This role requires a practitioner mindset grounded in hands-on data engineering or data science experience
- Candidates should be comfortable shaping technical direction based on community and user input
- Collaboration with distributed teams is a regular part of the role
- The position involves direct influence on the evolution of core developer tools and integrations
