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Sr. Delivery Solutions Engineer

Databricks
San Francisco, United Statesfull_timeVerifiedPosted 8 Feb 2024
💰 $204,800/yr($115,800/yr$204,800/yr)

About the role

Delivery Solutions Architect

 

Mission:

At Databricks we are on a mission to empower our customers to solve the world's toughest data problems by utilizing the Lakehouse platform. As a Delivery Solutions Architect (DSA), you will play a critical role during this journey. You will collaborate with our sales and field engineering teams to accelerate the adoption and growth of the Databricks platform in your accounts. As a DSA, you will help ensure customer success by driving focus and technical accountability to our most complex customers who need guidance to accelerate consumption on Databricks workloads that they have already selected.

This is a hybrid technical and commercial role. It is commercial in the sense that you will be required to own and drive growth in your assigned customers and use cases through leading your customers’ stakeholders, owning executive relationships and creating and driving plans and strategies for Databricks colleagues to execute upon. This is in parallel to being technical, with expectations being that you become at least Level 200 across all Databricks products/workloads and that you become the Use Case-specific technical lead post Technical Win. This requires you to utilize relationship management skills and technical credibility to engage and communicate at all levels with an organization effectively. You will report directly into a DSA manager as part of your Business Unit’s Technical GM organization. 

Your day to day responsibilities:

  • Engage with the Solutions Architect to understand the full Use Case Demand Plan for prioritized customers.
  • Own the Post-Technical Win technical account strategy and investment 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/ambiguity 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 point of contact for any technical issues or questions related to production/go live status of agreed-upon use cases within an account, often serving multiple use cases within the largest and most complex organizations. 
  • Leverage both Shared Services of User Education, Onboarding/Technical Services and Support resources, along with escalating to Level 400/500 technical experts (Specialist Solution Architects and Product Specialists) to execute on the right tasks that are beyond your scope of activities or expertise. 
  • Create, own and execute a PoV as to how key use cases can be accelerated into production, bringing EM/PM in to prepare Professional Services proposals.
  • Navigate Databricks Product and Engineering teams for New Product Innovations, Private Previews and Upgrade needs (DBR, E2 and Unity Catalog). 
  • Build and maintain mutual success plan that covers all activities of Customer, PS, Partner, SSA, Product Specialist, SA to cover the below workstreams:
    • Key use cases moving from ‘win’ to production
    • Enablement / user growth plan
    • Product adoption (strategy and activities to increase adoption of LH vision)
    • Organic needs for current investment Eg. Cloud Cost control, Tuning & Optimization
    • Executive and operational governance
  • Proactively provide internal and external updates - KPI reporting on the status of consumption and customer health, covering investment status, key risks, product adoption and use case progression - to your Technical GM.

What we look for (Competencies):

  • 5+ years in a customer-facing pre-sales, technical architecture, customer success, or consulting role
  • Experience understanding architecture related distributed data systems, specifically within one of the following:
    • Data Engineering technologies (e.g. Spark, Hadoop, Kafka)
    • Data Warehousing (e.g. SQL, OLTP/OLAP/DSS)
    • Data Science and Machine Learning technologies (e.g. pandas, scikit-learn, HPO)
  • Comfortable managing multiple projects at once, and engaging a virtual team of subject matter experts to address any onboarding or technical challenges outside of your remit or bandwidth.
  • Influencing and leading teams - especially without having direct reporting line responsibility for individuals within account and leadership teams, both internally and externally
  • Stakeholder management - experience in effectively engaging and influencing a variety of audiences (technical, non technical) at all levels of an organization (CxO to developer)
  • Executive escalation management - experience in resolving complex and critical escalation

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Company

Databricks

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