Databricks is the data and AI company, and they are seeking a Partner Engineer for Data Collaboration. In this role, you will act as a technical specialist supporting strategic partners in architecting and building their data collaboration strategy on Databricks, while also driving adoption of Databricks Marketplace and Delta Sharing.
Responsibilities:
- Lead end-to-end technical engagements with partners including onboarding, POC execution, data product evaluation, and Marketplace listing enablement
- Design and prototype cross-cloud Delta Sharing architectures including governance, entitlements, security patterns, recipient management, and network configuration
- Build and validate hands-on demos, sample data products, MCP server integrations, REST catalog validations, and multi-cloud sharing workflows
- Troubleshoot complex data-sharing issues across security, networking, metadata, and client integration
- Co-develop data productization strategies including metadata enrichment, semantic models, metric views, and AI-ready packaging
- Contribute to the evolution and rollout of the Partner Well Architected Framework, ensuring data collaboration best practices are up-to-date and informed by real partner experiences
- Act as a technical validator for new Databricks and partner features, providing actionable feedback to product and engineering teams
- Enable and educate partners and field teams on best practices for data collaboration, sharing, and Marketplace operations; develop training and documentation as needed
- Support the field on data sharing and collaboration use cases at their customers
Requirements:
- 5+ years experience in field engineering, solution architecture, or a technical cloud/data domain
- Experience with cloud data platforms (Databricks, AWS, Azure, GCP), data governance, and collaborative data product development
- Hands on Experience with data sharing, Delta Sharing, Unity Catalog, and associated Marketplace features preferred
- Strong written and verbal communication, consultative skills, and ability to manage technical partner relationships
- Comfort supporting multiple projects and navigating ambiguity; strong bias for hands-on execution and learning
- Experience working directly with large data providers, especially in managed sharing, collaborative delivery models, and data marketplaces
- Evangelist who can create excitement with the field and customers
- Industry experience in martech or healthcare
- Experience is customer facing roles working with data products
- Open-source contributions or community engagement in data and AI technologies