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Databricks

Builds cloud software for data analysis and AI

Senior Deployment Strategist - Multiple Teams

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeUnited States

About the Job

Requirements

  • Typically 7+ years of experience delivering complex, customer-facing data, analytics, artificial intelligence, or software engagements, or equivalent experience as a founder or technical builder.
  • Experience delivering data, machine learning, or generative artificial intelligence systems into production and understanding integration, operational, and adoption challenges in real environments.
  • Ability to define product requirements, prioritize engineering work, manage scope, and lead complex agile software projects from ambiguous problems to measurable outcomes.
  • Understanding of modern data and artificial intelligence architectures, including cloud platforms, data pipelines, data models, distributed systems, application programming interfaces, security and governance, machine learning, and generative artificial intelligence application patterns.
  • Proficiency in at least one programming language, such as Python, Java, or SQL.
  • Ability to explore data, work in notebooks, read and review code and pipelines, build or adapt prototypes, and contribute to troubleshooting.
  • Ability to build trust with senior stakeholders, communicate effectively, and help them make difficult decisions.
  • Willingness to work onsite with customers, often 25–50% of the time and sometimes more.

Responsibilities

  • Partner with Sales to conduct deep discovery, map customer organizations, quantify the business value of high-value problems, and define pilots, including their minimum viable products, success criteria, and timelines.
  • Own product direction for customer engagements from initial discovery through production launch and adoption.
  • Author product requirements documents, prioritize engineering backlogs, manage scope, and perform hands-on quality assurance testing.
  • Translate business requirements into data, integration, security, and operational requirements for engineering teams.
  • Drive the forward-deployed engineering build team through an agile delivery process, manage stakeholders from executives to individual engineers, and resolve technical or organizational blockers.
  • Lead technical discovery and design reviews; understand customer data flows, integrations, platform constraints, and operational environments; assess architecture choices; and identify technical risks.
  • Own launch readiness, manage launch war rooms, and drive solutions from launch to adoption by gathering user feedback, iterating, and demonstrating business value.
  • Own production readiness across data quality, testing, security, performance, and operations; work with the team to diagnose and resolve issues.
  • Scope ongoing maintenance plans, create customer documentation and training, and identify subsequent high-value engagements.
  • Codify reusable solution patterns and bring field insights to Product and Engineering.

Desired Qualifications

  • Experience in a high-growth technology company, forward-deployed organization, or leading consultancy.

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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