Minimum qualifications:- Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
- 2 years of coding experience in C/C , Java, Python, or Go.
- 2 years of experience architecting and developing large-scale distributed systems.
- 2 years of experience in concurrency, multithreading and synchronization.
Preferred qualifications:- Master's degree or PhD in Computer Science or related technical fields.
- 2 years of experience working on data infrastructure product or data infrastructure team.
- 2 years of experience with API and language design.
- Experience programming in C .
- Ability to do backend infrastructure work, comfortable with distributed systems and strong in system development (C ).
About the jobMake every decision data-driven by providing the safe, easy, reliable and fast way to query structured data.
The Core team builds the technical foundation behind Google's flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google's products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Enhance F1 Execution Kernel with advanced query features, making them accessible across all data sources and query stacks, including F1 and Table Services.
- Work on UTM, representing table metadata that powers query planning and data processing for various core data intelligence products such as F1, Conduit, Sawmill, and Napa, and serves as a vital component for the F1 Execution kernel and table API ecosystems.
- Address disk space limitations in AI/ML, improve agent performance, and transform F1 Query into a unified interface for federated vector and structured queries of first-party data.
- Contribute as a key member of the team, actively participating in code reviews, design discussions, and knowledge sharing.
