About this role
RDQ427R152
About the Role
As a Partner Engineer for Data Collaboration, you act as a technical specialist supporting strategic partners as they architect and build their data collaboration strategy on Databricks. You will prototype, evaluate, and implement best practices for data sharing, governance, and data productization, working directly with partner data teams to drive adoption of Databricks Marketplace, Delta Sharing, and Databricks native architectures.
Key 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
Required Qualifications
- 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.
Preferred Qualifications
- 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.
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.
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, please visit https://www.mybenefitsnow.com/databricks.
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.
Other facts
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and over 60% of the Fortune 500 — rely on Databricks to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified Data Intelligence Platform that includes Agent Bricks, Lakeflow, Lakehouse, Lakebase and Unity Catalog.
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Databricks applicants
Please apply through our official Careers page at databricks.com/company/careers.
All official communication from Databricks will come from email addresses ending with @databricks.com or @goodtime.io (our meeting tool).
What you'll do
- Lead technical engagements with partners to support their data collaboration strategies. Design and prototype architectures for data sharing and governance while troubleshooting complex issues.
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