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Lead strategic enterprise sales for Databricks’ Data Intelligence Platform within a focused enterprise account. Build relationships with CIOs and business leaders, expand usage across business units, drive value-based growth, exceed pipeline and revenue targets, manage forecasts in Salesforce, and develop internal and customer success plans. The role requires selling big data, cloud, SaaS, analytics, and AI solutions to large accounts using a consumption-based model.

Lead analyst relations programs to improve Databricks’ positioning in industry evaluations, including Gartner, Forrester, and IDC. Develop differentiated narratives, submissions, demonstrations, customer evidence, and executive briefings. Scale analyst relations through AI-assisted workflows, convert analyst feedback into product and go-to-market recommendations, and influence product, marketing, sales, and executive teams. Manage multiple deadline-driven workstreams while improving analyst advocacy, market visibility, and evaluation outcomes.

The Director, AI Sales will grow Databricks’ enterprise AI business by driving strategic account adoption, production usage, bookings, and consumption. Responsibilities include developing AI sales plays, enabling field teams, securing executive and technical sponsorship, advancing complex opportunities, coordinating sales and partner stakeholders, and translating customer feedback into product and go-to-market recommendations.

Drive enterprise sales of Databricks’ cloud data platform across new and existing accounts. Develop territory plans, engage CIOs and other senior decision-makers, manage complex sales cycles, identify opportunities, exceed pipeline and revenue targets, maintain Salesforce forecasting data, and use solution-based selling to communicate the value of Databricks, Apache Spark, and big data technologies.

Lead GTM compensation strategy and programs: design pay frameworks, manage lifecycle compensation processes, analyze market and comp data, advise founders and senior leaders, and scale enterprise-wide compensation solutions.

Build and grow Databricks’ CustomerLake sales business across enterprise and strategic accounts. Partner with Account Executives to develop pipeline, engage CMOs and marketing leaders, lead complex evaluations and negotiations, create quantified business cases, and drive adoption and revenue. The role also develops repeatable sales plays, enables field teams and partners, and shapes the emerging CustomerLake sales strategy.

Leads global pipeline strategy, executive pipeline governance, and Sales Development capacity planning. Builds pipeline targets, coverage models, operating cadences, compensation frameworks, and career architecture for xDR teams. Partners cross-functionally across Sales, Marketing, Partnerships, Product GTM, and Programs to improve pipeline generation and executive decision-making. Uses AI, automation, analytics, and strategic reporting to optimize workflows, productivity, and account coverage.

Lead Databricks’ global Genie sales organization, driving revenue growth, pipeline, enterprise adoption, and repeatable sales plays. Recruit and develop specialist sellers, coach complex enterprise deals, engage executive stakeholders, and partner with account teams, product, engineering, marketing, cloud providers, systems integrators, and ISVs. Shape product and go-to-market strategy while positioning Genie as a conversational analytics and enterprise data intelligence platform.

Leads technical strategy for customer accounts by designing scalable data, AI, streaming, and analytics architectures. Advises senior technical stakeholders, drives Databricks adoption and consumption, supports competitive technical wins, coordinates cross-functional resources, and provides product feedback. The role requires strong Python and SQL coding, distributed data systems expertise, public cloud deployment experience, and the ability to communicate architecture and business value effectively.

Build and maintain AI-native skills taxonomies, capability models, learning context, instrumentation, and APIs for Databricks employees, customers, and partners. Develop LLM-driven extraction, agentic pipelines, drift and gap detection, and live capability measurement. Partner across content, curriculum, certification, product, and enablement teams to ensure technical skills are consistently defined, assessed, and applied. Use Python, SQL, analysis, and clear writing to advance strategy as an individual contributor.