Delivery Solutions Architect - Startups & Emerging Enterprise
About the role
As a Delivery Solutions Architect (DSA), you will play an important role in accelerating the adoption and growth of the Databricks platform with Startup and Emerging Enterprise customers. You will collaborate with sales and field engineering teams to ensure customer success by helping complex customers maximize the value of the Databricks platform and their return on investment.
Responsibilities
- Engage with Solutions Architects to understand the full use case demand plan for prioritized customers
- Lead the post-technical-win account strategy and execution plan for the majority of Databricks use cases within our most strategic accounts
- Be the accountable technical leader for specific use cases and customers across multiple selling teams and internal stakeholders, creating certainty from uncertainty and driving onboarding, enablement, go-live, and healthy consumption of the workloads the customer has chosen to run on Databricks
- Create, own, and execute a point of view on how key use cases can be accelerated into production, coordinating with Professional Services (PS) resources on the delivery of PS Engagement proposals
- Partner with Databricks Product and Engineering teams on new product innovations, private previews, and upgrades
- Develop an execution plan spanning all customer-facing technical roles and teams across the following work streams: Main use cases moving from 'win' to production, Enablement / user growth plan, Product adoption (strategy and activities to increase adoption of Databricks' Lakehouse vision), Organic needs for current investment (e.g. cloud cost control, tuning & optimization), Executive and operational governance
- Provide internal and external updates to your Technical GM — KPI reporting on usage and customer health, covering investment status, key risks, product adoption, and use case progression
Requirements
- 5+ years of experience accountable for technical project / program delivery in Data and AI, with the ability to contribute to technical debate and design choices alongside customers
- Programming experience in Python, SQL or Scala
- Experience in a customer-facing pre-sales, technical architecture, customer success, or consulting role
- Understanding of solution architecture for distributed data systems
- Understanding of how to attribute business value and outcomes to specific project deliverables
- Technical program or project management, including accountability for accounts, stakeholders, and resources
- Experience resolving complex, high-stakes escalations with senior customer executives
- Experience conducting open-ended discovery workshops, creating strategic roadmaps, conducting business analysis, and managing delivery of complex programs/projects
- Track record of overachievement against quota, goals, or similar objective targets
Qualifications
- Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience
- Can travel up to 30% when needed
Skills
- Technical credibility to engage and communicate at all levels within an organization
- Ability to leverage Shared Services, User Education, Onboarding/Technical Services, and Support resources, and escalate to subject matter experts when work falls beyond your scope or expertise
- Ability to develop and own a point of view on how key use cases can be accelerated into production
- Ability to partner with Databricks Product and Engineering teams on new product innovations, private previews, and upgrades
- Ability to develop and execute an execution plan spanning all customer-facing technical roles and teams across various work streams
Benefits
The benefits offered at Databricks include comprehensive coverage, including 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.
Pay Range
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.