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.
- Operational Excellence: Ensure the reliability and efficiency of our cost-management systems as they integrate into our core infrastructure.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Local Pay Range
$228,600—$314,250 USD
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
**Benefits
**At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.