Principal Engineer, Compute Fleet Management

Databricks•Bellevue, WA

10d

About The Position

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. About the Team: Join the Core of Databricks Infrastructure The Compute Infra Team is the engine behind all of Databricks' products and Control Plane services. We build and scale the foundational compute infrastructure that enables every Databricks customer to succeed, operating one of the largest and most dynamic data and AI clouds in the world. Mission: Define the Future of Cloud Compute Efficiency and Scale As the Technical Lead for Compute Fleet Management, you won't just manage a fleet—you will set the standard for how Databricks consumes and optimizes compute across all three major clouds (AWS, Azure, and GCP). This is a mission-critical role with direct impact on our gross margin and customer experience. Your mandate includes: Pioneering Fleet Optimization: Provisioning and pooling of O(Billion)s of cloud resources to achieve peak workload performance, industry-leading efficiency, and robust resource isolation. Delivering Hyper-Scale Resilience: Build the architecture that guarantees horizontal scaling and resilience against zonal or even cloud account-level failures, ensuring Databricks is always on. Owning the Critical Path: Lead the development of the lowest-dependency systems required to bootstrap and manage our massive compute platform. Outcomes: The Impact You Will Deliver This role is for an engineer who thrives on owning the most challenging and impactful outcomes: High Availability: Achieve and maintain 99.99% availability for all batch and serving workloads. Stellar Efficiency: Drive utilization to 60% or higher—a crucial metric that requires balancing high efficiency with unwavering tolerance for cloud failures. Best-in-Class Isolation: Architect and enforce strong security and performance isolation across a diverse range of customer workloads.

Requirements

Leading Transformative Projects: Taking ownership of complex, cross-team, cross-layer, and multi-quarter strategic engineering initiatives from concept to execution.
Distributed Systems Mastery: Deep, hands-on experience developing and operating high-scale distributed systems on at least one major public cloud.
Influence Without Authority: Proven ability to drive consensus, establish technical direction, and lead large technical efforts across organizational boundaries.
Execution Discipline: Exceptional strength in planning, tracking project progress, and managing complex cross-organizational dependencies.

Nice To Haves

Experience managing and scaling a massive fleet of GPUs for AI/ML workloads.
Experience with developing and operating large-scale distributed systems across all major clouds (AWS, Azure, and GCP).

Responsibilities

Pioneering Fleet Optimization: Provisioning and pooling of O(Billion)s of cloud resources to achieve peak workload performance, industry-leading efficiency, and robust resource isolation.
Delivering Hyper-Scale Resilience: Build the architecture that guarantees horizontal scaling and resilience against zonal or even cloud account-level failures, ensuring Databricks is always on.
Owning the Critical Path: Lead the development of the lowest-dependency systems required to bootstrap and manage our massive compute platform.
Achieve and maintain 99.99% availability for all batch and serving workloads.
Drive utilization to 60% or higher—a crucial metric that requires balancing high efficiency with unwavering tolerance for cloud failures.
Architect and enforce strong security and performance isolation across a diverse range of customer workloads.

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