Databricks
Delivery Solutions Architect - High-Tech & Manufacturing
United States. Posted 6 months ago
The role
You will collaborate with sales and field engineering teams to accelerate Databricks platform adoption and growth. You will act as a post-sale technical lead to ensure customer success and maximize value from Databricks workloads.
What you will do
- Engage with Solutions Architects to understand use case demand plans
- Lead post-technical win technical account strategy and execution
- Drive onboarding, enablement, success, and healthy consumption of workloads
- Act as first contact for technical issues related to production status
- Leverage Shared Services, User Education, and Support resources
- Execute plans to accelerate key use cases into production
- Navigate Databricks Product and Engineering teams for innovations and upgrades
- Develop execution plans for use case production, enablement, and product adoption
- Provide internal and external KPI reporting on usage and customer health
Required qualifications
- 5+ years of experience in technical project/program delivery within Data and AI
- Programming experience in Python, SQL, or Scala
- Experience in customer-facing pre-sales, technical architecture, customer success, or consulting
- Understanding of solution architecture related to distributed data systems
- Understanding of how to attribute business value and outcomes to specific project deliverables
- Technical program or project management experience
- Experience in resolving complex escalations with senior customer executives
- Experience conducting discovery workshops, creating roadmaps, and managing complex programs
- Track record of overachievement against quota, goals, or similar objective targets
- Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience
- Ability to travel up to 30% when needed
About the company
Databricks is the Data and AI company. More than 20,000 organizations worldwide rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents.