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Databricks

Builds cloud software for data analysis and AI

Delivery Solutions Architect

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Programming experience in PySpark, Python, and Databricks or a similar data platform.
  • Understanding and hands-on experience with solution architecture for distributed data and analytics systems.
  • At least 5 years of experience being accountable for delivery of Data, Analytics, or AI projects and contributing to technical debate and design choices with customers.
  • Experience in customer-facing pre-sales, technical architecture, customer success, or consulting roles.
  • Understanding how to attribute business value and outcomes to specific project deliverables.
  • Experience with technical program coordination, including account and stakeholder management.
  • Experience resolving complex, important escalations with senior customer technical stakeholders.
  • A track record of overachievement against quota, goals, or similar objective targets.
  • A bachelor's degree in Computer Science, Information Systems, or Engineering, or equivalent experience through work experience.
  • Ability to travel up to 30%.

Responsibilities

  • Serve as the Databricks Architect working with customer technical teams on use cases and data products from development through go-live, addressing technical challenges and blockers and providing guidance, best practices, and enablement.
  • Lead the post-technical-win technical account strategy and execution plan for most Databricks use cases within strategic accounts.
  • Act as the internal point of contact for production and go-live status questions on agreed use cases within an account, often across multiple use cases in large and complex organizations.
  • Leverage Shared Services, User Education, Onboarding/Technical Services, and Support resources, and escalate tasks beyond the role's scope or expertise to expert-level technical teams.
  • Create and execute points of view on accelerating key use cases into production, coordinating with Professional Services resources on delivery proposals.
  • Navigate Databricks Product and Engineering teams for product innovations, private previews, and upgrade needs, presenting these to customers when applicable.
  • Provide internal and external updates and KPI reporting to Field Engineering leadership on usage and customer health, risks and blockers, product adoption, and use-case progression.

About the Company

Databricks

Builds cloud software for data analysis and AI

Databricks builds cloud software that businesses use to organize data, analyze it, and develop AI applications. Its lakehouse architecture brings the flexible storage of a data lake together with the querying and management tools of a data warehouse. Data engineers prepare and update datasets, analysts build reports, and developers train models or create applications in a shared workspace with controls over who can use the data. The platform runs on Amazon, Microsoft, and Google clouds, and customers pay for computing usage or commit to longer contracts for discounted rates. Databricks was founded in 2013 and is headquartered in San Francisco, California.

Company size
10,001+
Company stage
Late Stage VC
Total funding
$32.1B
Headquarters
San Francisco, CA
Founded
2013

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