Sr. Technical Program Manager, FDE
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
About the Role
You will lead customer technical projects delivering production-grade systems, reference architectures, custom applications and ML/AI integrations. You will guide strategic customers through big data and AI implementations, own architecture decisions, scope delivery work with engagement managers, and give product feedback to Engineering and Support. Travel to customers about 20% of the time.
Requirements
- 6+ years in data engineering, data platforms & analytics, or software engineering
- Coding in Python, Scala, JavaScript/TypeScript and modern frameworks
- Working knowledge of two or more cloud ecosystems (AWS, Azure, GCP)
- Deep experience with Apache Spark and runtime internals
- Familiarity with CI/CD
- Working knowledge of MLOps, ML/AI models and AI APIs
- Experience with technical project delivery
- Documentation and white-boarding skills
- Experience with enterprise clients and stakeholder conflicts
- Travel to customers 20% of the time
- Databricks Certification
Responsibilities
- Lead customer technical projects delivering production-grade systems and reference architectures
- Guide strategic customers through end-to-end big data and AI implementations
- Scope technical delivery work with engagement managers
- Guide customers on architecture and design to drive Databricks adoption
- Lead architecture and design decisions
- Work with technical team, Project Manager, Architect and customer team on delivery
- Provide product feedback to Engineering and Customer Support
- Embed with customer teams
- Contribute accelerators, frameworks and best practices