Delivery Solutions Architect
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
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will be the Databricks architect for customer technical teams, guiding use cases from development to go-live. You will lead post-win account strategy, act as the point of contact for production questions, coordinate with Professional Services and Product teams, and report on usage and customer health. This is not a hands-on-keyboard role but is highly technical.
Requirements
- Programming experience in PySpark, Python and Databricks or similar platform
- Hands-on understanding of distributed data and analytics solution architecture
- 5+ years accountable for delivery of Data, Analytics or AI projects
- Experience in customer-facing pre-sales, technical architecture, customer success or consulting
- Ability to attribute business value to project deliverables
- Technical program coordination and stakeholder management
- Experience resolving escalations with senior customer technical stakeholders
- Track record of overachievement against quota or goals
- Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience
- Can travel up to 30%
Responsibilities
- Work with customer technical teams on use cases from development to go-live, resolving blockers and providing best practices
- Lead post-technical-win account strategy and execution plan
- Be the internal point of contact for production and go-live questions
- Leverage shared services and escalate to expert technical teams
- Create and execute a point of view to accelerate use cases into production
- Navigate Product and Engineering teams and present innovations to customers
- Provide KPI reporting on usage and customer health to Field Engineering leadership
