Sr. Delivery Solutions ArchitectNew

Databricks
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The opportunity

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents.

What you'll do

  • Engage with Solutions Architects to understand the full use case demand plan for prioritised customers

  • Lead the post-technical win technical account strategy and execution plan for: the majority of Databricks use cases within our most strategic accounts

  • Be the accountable technical leader assigned to specific use cases and: customer(s) across multiple selling teams and internal stakeholders, creating certainty from uncertainty and driving onboarding, enablement, success, go-live and healthy consumption of the workloads where the customer has made the decision to consume 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, oftentimes services multiple use cases within the largest and most complex organizations

  • Leverage both Shared Services, User Education, Onboarding/Technical Services: and Support resources, along with escalating to expert level technical experts to build the right tasks that are beyond your scope of activities or expertise

  • Create, own and execute a point-of-view as to how key use cases can be: accelerated into production, coordinating with Professional Services (PS) resources on the delivery of PS Engagement proposals

What they're looking for

  • Navigate Databricks Product and Engineering teams for new product: Innovations, private previews and upgrade needs
  • Develop an execution plan that covers all activities of all customer-facing: technical roles and teams to cover the below 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)