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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-timeSeoul, South KoreaNo salary listedIn-person

About the Job

Requirements

  • At least 8 years of experience in a customer-facing pre-sales, technical architecture, customer success, or consulting role.
  • Experience understanding architecture related to distributed data systems, specifically in data engineering technologies such as Spark, Hadoop, or Kafka; data warehousing such as SQL, OLTP, OLAP, or DSS; or data science and machine learning technologies such as pandas, scikit-learn, or HPO.
  • Ability to manage multiple projects simultaneously and engage a virtual team of subject matter experts to address onboarding or technical challenges outside the role's remit or bandwidth.
  • Experience influencing and leading teams without direct reporting-line responsibility for individuals in account and leadership teams, internally and externally.
  • Experience engaging and influencing technical and non-technical audiences at all organizational levels, particularly building and maintaining C-suite relationships.
  • Experience resolving complex, critical escalations with senior customer and internal executives.
  • Experience conducting open-ended discovery workshops, creating strategic roadmaps, conducting business analysis, and managing delivery of complex programs or projects.
  • Experience building and steering a value case through business value consulting and realization.
  • Quota ownership, achievement, and a track record of strong performance against objective targets.
  • Native-level spoken and written Korean and business-level spoken and written English.

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 most Databricks use cases within strategic accounts.
  • Serve as the accountable technical leader for assigned use cases and customers across selling teams and internal stakeholders, driving onboarding, enablement, success, go-live, and healthy workload consumption.
  • Act as the first point of contact for technical issues or questions related to the production or go-live status of agreed use cases within an account, often across multiple use cases in large, complex organizations.
  • Leverage User Education, Onboarding/Technical Services, and Support resources, and escalate to Level 400/500 technical experts, including Specialist Solution Architects and Product Specialists, for tasks beyond the role's scope or expertise.
  • Create, own, and execute a proof of value to accelerate key use cases into production, involving engineering managers and product managers to prepare Professional Services proposals.
  • Navigate Databricks Product and Engineering teams for new product innovations, private previews, and upgrades involving DBR, E2, and Unity Catalog.
  • Build and maintain executive-level and detailed program-level success plans covering customer, Professional Services, partner, Specialist Solution Architect, Product Specialist, and Solutions Architect activities for use cases moving from win to production; enablement and user growth; product adoption; cloud cost control, tuning, and optimization; and executive and operational governance.
  • Provide internal and external status updates and KPI reporting to the Technical GM on consumption and customer health, investment status, key risks, product adoption, and use-case progression.
  • Develop reusable, scalable assets and mentor junior team members to establish the DSA team.

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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