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The role involves creating and managing large-scale data and AI products, focusing on user experience, and leading significant engineering efforts.

The role involves defining and owning the product vision and strategy for compute platform features, collaborating with engineering and engaging with customers to drive product success.

Run and own AI-first sales development programs: design metrics, reporting, governance, adoption, and sequence management. Drive executive cadences, prioritize with sales leaders, build data foundations and field-facing reporting, and partner across AI Ops, Sales Ops, GTM Analytics, and Enablement to scale AI-native prospecting.

Lead GEO and AI search optimization to increase Databricks' visibility and citations across AI answer engines and organic search. Build experimentation programs, publish AI-citable technical content, maintain technical SEO health (schema, crawlability, Core Web Vitals), and partner cross-functionally to drive traffic, conversions, and pipeline while delivering executive reporting and a repeatable GEO playbook.

Lead and scale Databricks' global web marketing function: build a product-focused team, modernize web properties for humans and AI agents, implement personalization and testing, apply AI to automate web workflows, ensure machine-readable content and strong information architecture, drive analytics-informed growth, manage vendors, and coordinate global marketing efforts.

Design and maintain a skill and concept graph, build ML models to infer learner skills, and develop recommendation systems and LLM-driven features. Ship production-ready LLM systems, define explainability standards, partner with frontend and product teams, and monitor model performance and evaluation frameworks.

Build and lead a global Generative Engine Optimization function to increase Databricks visibility across AI answer engines and organic search. Own strategy, experimentation, measurement, technical SEO, cross-functional execution, and hiring to drive AI-referred traffic, conversions, and pipeline.

Serve as a customer-facing technical advisor for Databricks on Azure, designing and deploying secure, scalable enterprise architectures, building PoCs, automating infrastructure with IaC, and supporting pre/post-sales technical engagements while sharing knowledge through tutorials and community contributions.

Lead end-to-end technical strategy and architecture for accounts, drive Databricks platform adoption, design scalable data and ML/streaming solutions, advise senior technical stakeholders, coordinate cross-functional teams, influence product direction, and support production deployments on public cloud.

The Emerging Enterprise Sales Leader will oversee a team focused on selling to the Emerging Enterprise Segment, driving revenue success, building strategic plans, and developing long-term customer relationships.