Engineering Manager - Developer Ecosystem
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
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
About the Role
You will lead a team of senior engineers building the declarative deployment framework, including the deployment engine and open-source CLI, in-workspace authoring and deployment experience, and deployment history and metadata. You will set the roadmap with Product and Design, make agentic development the default path, own reliability and delivery, and manage backward compatibility.
Requirements
- 3+ years managing software engineering teams and 8+ years of software engineering experience
- Track record of shipping developer tools or platforms such as IaC, CI/CD, CLIs, SDKs
- Deep understanding of declarative systems and deployment workflows: plan/apply, state management, drift, GitOps
- Technical depth to engage on architecture and trade-offs
- Experience leading teams through ambiguity
- Strong product sense and customer-first mindset
- Excellent written and verbal communication
Responsibilities
- Lead, hire, coach and promote a team of senior engineers
- Shape how developers and AI agents author, validate and deploy projects
- Own strategy and multi-quarter roadmap with Product and Design
- Run predictable delivery, reliability, on-call health and incident response
- Lead engine and configuration migrations while maintaining backward compatibility
- Drive alignment across platform teams and Developer Ecosystem teams