Delivery Solutions Architect - Startups & Emerging Enterprise

OpenTalent; United States; Hybrid; USD 140,000 - 200,000; Full time

Job summary

Databricks is seeking a Delivery Solutions Architect to serve as the post-sale technical lead across all Databricks products. You will collaborate with sales and field engineering teams to accelerate adoption among Startup and Emerging Enterprise customers and ensure maximum ROI from the platform.

This is a hybrid technical and commercial role where you will drive growth by leading customer stakeholders, orchestrating teams, and creating plans for Databricks colleagues to build upon.

Responsibilities

• Engage with Solutions Architects to understand use case demand plans.
• Lead post-technical-win strategy and execution for strategic accounts.
• Be accountable technical leader across multiple selling teams for specific use cases.
• Be first contact for technical issues related to production/go-live status.
• Leverage Shared Services and PS resources; elevate to SMEs when needed.
• Create and execute a point of view on accelerating use cases into production with PS engagement proposals.
• Partner with Product and Engineering on new product innovations and upgrades.
• Develop execution plans across customer-facing technical roles and teams for production adoption.

Job description

At Databricks, we are on a mission to empower our customers to solve the world's toughest data problems by utilizing the Databricks Data Intelligence Platform. As a Delivery Solutions Architect (DSA), you will play an important role during this journey. You will collaborate with our sales and field engineering teams to accelerate the adoption and growth of the Databricks platform with Startup and Emerging Enterprise customers. You will also help ensure customer success by helping our most complex customers maximize the value they get out of our platform and their return on investment.

This is a hybrid technical and commercial role. It is commercial in the sense that you will drive growth in your assigned customers and use cases by leading your customers' stakeholders, building executive relationships, orchestrating other focused/specialized teams within Databricks, and creating and driving plans and strategies for Databricks colleagues to build upon. It is technical in the sense that you will serve as the post-sale technical lead across all Databricks products. This requires you to use your skills and technical credibility to engage and communicate at all levels within an organization. You will report directly to a DSA Manager within the Field Engineering organization.

The impact you will have:

• 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
• Be the first contact for any technical issues or questions related to production/go live status of agreed upon use cases within an account, often spanning multiple use cases within the largest and most complex organizations
• Leverage Shared Services, User Education, Onboarding/Technical Services, and Support resources, and elevate to subject matter experts when work falls beyond your scope or expertise
• 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