Senior Manager Infrastructure Data Science
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Maintainer signals as of 9/23/2026
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead data scientists and partner with engineering leaders to deliver data-driven infrastructure insights and solutions. You will guide capacity planning, performance optimization, reliability engineering, risk mitigation, resource efficiency, and support data frameworks while mentoring your team.
Requirements
- 10+ years of infrastructure data science, machine learning, or advanced analytics experience
- 5+ years of management experience hiring and developing teams
- Experience developing data science, analytics, machine learning, and AI products in cloud environments
- Knowledge of statistics and rigorous analytical techniques
- Experience with data visualization, data engineering, data modeling, and big data technologies
- Leadership across functional and organizational lines
- Communication skills for explaining analytics and data science to executives and senior management
- MS or Ph.D. in Statistics, Mathematics, Computer Science, or Engineering
Responsibilities
- Provide strategic guidance on infrastructure planning and growth projections
- Promote data-driven infrastructure decisions across engineering
- Implement solutions to identify, predict, and mitigate infrastructure risks and failures
- Analyze resource utilization to improve efficiency and performance
- Establish data frameworks that help support teams resolve product issues faster
- Mentor and manage data scientists
- Instill data science and engineering best practices
Benefits
- Eligibility for annual performance bonus
- Equity
