- Mountain View, California, United States
- Hybrid
- Full-time · Staff
- $231K–$378K per year
- 10+ years
A highly technical leadership role focused on database performance and efficiency optimization across online and offline data infrastructure, specifically focusing on relational systems and large-scale distributed systems.
Compensation
$231,000 to $378,000
Responsibilities
- Set technical direction for database performance and efficiency optimization across LinkedIn’s online and offline data infrastructure.
- Lead improvements to database and offline systems, including query planning and execution, indexing, storage, and application access patterns.
- Diagnose performance bottlenecks across application, database, and storage layers, and drive improvements in latency, throughput, resource utilization, and infrastructure cost.
- Extend optimization approaches across offline analytical, nearline, streaming, and batch systems, identifying opportunities to improve query execution and storage efficiency.
- Shape architectures that connect online transactional and offline analytical systems, including query federation and converged data platforms.
Requirements
- BA/BS degree in Computer Science or a related technical field
- Nice to have: Master’s or PhD in Computer Science
- Nice to have: query optimizers
- Nice to have: execution engines
- Nice to have: storage engines