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Customer-facing senior engineer who architects, implements, and productionizes end-to-end data and AI solutions on Databricks. Responsibilities include Spark-based distributed data engineering, ML/AI model integration, CI/CD deployments, technical project delivery, stakeholder engagement, reusable assets creation, and providing product/implementation feedback.

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.

Lead and execute global finance programs, owning planning, intake, prioritization, and cross-functional delivery. Drive accounting process optimization, SOX control implementation, automation opportunities, reporting, executive communications, and metrics to improve Controllership operations.