Sr Manager, Engineering- Cloud Intelligence & Infrastructure Economics

P-932

At Databricks, we are passionate about helping data teams 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. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

The Opportunity

Databricks is the leader in Data and AI, and our platform operates on a global scale. We are seeking a Senior Engineering Manager to lead the engineering team responsible for the Intelligence and Economics of our infrastructure.

In this role, you will build the Intelligent Governance and Efficiency layer that optimizes billions of dollars spent across all Databricks products in a complex multi-cloud environment . You will lead a high-caliber team of engineers to build the "financial nervous system" of Databricks, ensuring our most advanced technologies, including Generative AI and Serverless —scale with world-class unit economics.

The Mission: From Visibility to Autonomy

We are evolving our infrastructure from cost reporting to Autonomous Governance . You will own the roadmap to build platform-native systems that automatically manage, enforce, and optimize resources globally.

• Infrastructure Intelligence: Build high-scale data pipelines and attribution models that provide a "Source of Truth" for demand and capacity planning.

• Economic Orchestration: Engineer the automated enforcement layer—including budget quotas, anomaly detection, and self-healing remediation—to manage exploding GenAI and serverless costs.

• Margin Intelligence: Drive product-level margin attribution (Shared COGS, AI provider costs) to enable leadership to make data-driven roadmap and pricing decisions.

Job Requirements (What We Are Looking For)

• Bachelor’s Degree: Bachelor’s degree (or foreign equivalent) in Computer Science, Engineering, or a related technical field.

• Engineering Management Experience: 7+ years of experience in engineering management, specifically leading high-performance teams in an Infrastructure, Production Engineering, or Cloud Systems environment.

• Technical Breadth: 7+ years of experience with distributed systems architecture, including professional experience with Kubernetes and Cloud-native architectures (AWS, Azure, or GCP).

• System Design & Scale: Proven experience designing, building, and operating large-scale distributed systems that support high-availability SaaS platforms or services with millions of users.

• Software Development: Proficiency in professional software development using high-level languages such as Java, Scala, or C++.

• Platform Building: Demonstrated track record of architectural leadership in transitioning fragmented technical environments into unified, automated, and opinionated platforms.

Preferred Qualifications

• Master’s degree or PhD in Computer Science or a related field.

• Experience in "Infrastructure-as-Code" (Terraform, CloudFormation) and large-scale data orchestration.

• Background in Cloud Economics, Capacity Planning, or Fleet Efficiency at a global scale.

The Impact You Will Have

• Hire and Mentor: Scale a world-class engineering team in Mountain View, providing technical guidance and career development.

• Strategic Leadership: Collaborate cross-functionally with Product, Finance, and Data Science to define the economic future of the Databricks platform.

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