About the Role
You will develop and maintain SDKs that enable seamless dataframe interactions across multiple programming languages, ensuring performance, reliability, and ease of integration for end users.
Responsibilities
- Design and implement SDKs for dataframe manipulation in multiple languages
- Optimize data serialization and deserialization for high-throughput use cases
- Collaborate with core engineers to align SDK features with underlying data engine capabilities
- Maintain backward compatibility while introducing new functionality
- Write comprehensive unit and integration tests
- Document APIs and usage patterns for developer audiences
- Respond to community feedback and prioritize bug fixes
- Improve developer experience through intuitive API design
- Monitor performance metrics and identify bottlenecks
- Support documentation and example repositories
- Work with tooling teams to ensure consistent build and release processes
- Evaluate new language features and ecosystem changes for compatibility
- Participate in code reviews and maintain code quality standards
- Troubleshoot integration issues reported by users
- Contribute to open-source components where applicable
- Assist in defining roadmap priorities for SDK development
- Ensure type safety and error handling are consistent across bindings
- Integrate with CI/CD pipelines for automated testing and deployment
- Collaborate on schema evolution strategies for long-term data compatibility
- Stay current with trends in data processing and dataframe libraries
Nice to Have
- Contributions to open-source data libraries
- Experience with Apache Arrow or similar columnar formats
- Work on cross-platform SDKs with multiple language bindings
- Prior work with data visualization or debugging tools
- Familiarity with Rust or other memory-safe systems languages
- Experience in early-stage product development
- Knowledge of data serialization protocols like FlatBuffers or Cap'n Proto
- Background in observability or logging systems
- Participation in developer advocacy or technical writing
- Understanding of data privacy and security considerations
Compensation
Competitive salary and equity package
Work Arrangement
Remote-first with optional co-working spaces
Team
Small, autonomous team focused on developer tools and data infrastructure
Tech Stack
- Primary languages include Rust, Python, and TypeScript
- Use of Apache Arrow for in-memory data representation
- CI/CD via GitHub Actions and automated release pipelines
- Documentation hosted via static site generators
- Collaboration tools include GitHub, Slack, and Notion
Development Philosophy
- Focus on correctness, performance, and usability
- Commitment to open-source principles where applicable
- Iterative development with frequent user feedback
- Emphasis on type safety and compile-time guarantees
- Minimal runtime overhead by design
Available for qualified candidates
