Senior / Principal C++ Software Engineer, Data Engines

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 compute primitives, compute intermediate representation, query parser and optimizer and other foundational components.
• Diving into data processing engine architecture, how different components interact with each other and how data flows through a compute graph.
• Learning and embracing the Apache development process.

Within a month:

• Profiling query runs for data engines and analyzing the execution telemetry to better understand how query engines works.
• Diving deep into the various relational algebra algorithms to understand how they work and how they can be improved.
• Working with the team on fixing bugs, implementing simple optimizations or code refactoring projects. 

• Make small improvements to more sophisticated engine components such as resource management, task scheduling, and fault tolerance.

Within 6 months:

• Building new relational algebra components to expand SQL coverage or DataFrame functionality coverage.
• Making small improvements to more sophisticated engine components such as resource management, task scheduling, and fault tolerance.
• Helping systems improve by using more modular and composable components.

• Propose and implement core architecture improvements to engines components.

Within 12 months:

• Proposing and implementing core architecture improvements to engines components.
• Working on challenging tasks such as language agnostic user defined functions, multi-query concurrency, and multi-tenancy.
• Integrating engines with other components and features developed by other teams in the company to provide enterprise grade customer experiences.

• Lead core technical projects improving the engine architecture and performance.