Senior C++ Software Engineer, Storage

Why work at Voltron Data?

• We are Going for Impact: We are a Series A, venture-backed startup assembling a global team to build a new foundation for data analytics with Apache Arrow. This foundation will usher in a wave of innovation in data processing that can take full advantage of the speed and efficiency offered by modern hardware. 
• We are Committed to Bridging Open Source Communities: We are a collection of open source maintainers who have been driving open source ecosystems over the last 15 years, particularly in the C++, Python, and R programming ecosystems.
• We are Building a Diverse, Inclusive Company:  We are creating a representative, equitable, and respectful workplace that prioritizes employee growth. Everyone at Voltron Data is bought into the company’s success; all voices are critical to shaping the organization’s future. 

Timeline

Below is a rough timeline of where you can expect to be at different points during your career path starting in this position.

Upon joining:

• Spending time learning about the Apache Arrow memory layout, compute primitives, and APIs.
• Familiarizing yourself with the different partners for compute kernels and the query execution engine on Apache Arrow.
• Learning and embracing the Apache development process.

Within a month:

• Implementing new high-performance storage and I/O primitives.
• Benchmarking existing I/O library functions to determine where there are bottlenecks.
• Discovering and implementing optimizations in data reads and writes.
• Participating in peer code review of all PRs related to file storage and interacting with different filesystems.
• Contributing to technical discussions and technical design documents.

Within 6 months:

• Developing a comprehensive set of low level benchmarks for I/O functions targeting various local, networked and cloud storage technologies to enable monitoring for performance regressions.
• Ensuring that all filesystems interactions are compatible and performant across platforms (Linux, MacOS, and Windows).
• Identifying and building reusable software components to ensure a high quality and maintainable codebase.

Within 12 months:

• Analyzing I/O throughput in a massively parallel and distributed query engine to identify inefficiencies and crafting solutions to tackle those inefficiencies.
• Ensuring that the everything related to storage is built as high quality as possible, balancing performance, usability, and maintainability across the Voltron Data and Apache Arrow ecosystems.