Strategic AI/BI Account Executive

Databricks
London, United KingdomPosted 5 March 2026

Job Description

<p data-pm-slice="1 1 []">SLSQ327R186</p> <p data-renderer-start-pos="1648">While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered.</p> <ul> <li data-renderer-start-pos="1800">London </li> <li data-renderer-start-pos="1800">Munich</li> <li data-renderer-start-pos="1800">Amsterdam </li> <li data-renderer-start-pos="1800">Paris </li> </ul> <p>Databricks is seeking a Genie + AI/BI Sales Specialist to help enterprise customers transform how business users interact with data. This high-impact role sits within the AI Go-To-Market team and partners closely with Enterprise Account Executives to drive adoption of Databricks AI/BI and Genie. You will help organizations move beyond static dashboards to governed, conversational, AI-powered analytics at the center of the convergence of business intelligence, data platforms, and generative AI.</p> <p>Enterprise analytics is rapidly evolving from dashboards and static reporting to conversational, AI-driven decision platforms. Databricks AI/BI and Genie empower business users to securely interact with governed data using natural language, transforming the data platform into a true decision platform. If you want to be at the forefront of AI-powered analytics transformation at one of the fastest-growing data and AI companies in the world, this is your opportunity.</p> <p data-renderer-start-pos="2006"><strong data-renderer-mark="true">The impact you will have:</strong></p> <ul> <li>Partner with Enterprise AEs to identify, qualify, and close AI/BI opportunities</li> <li>Engage C-level, analytics, and line-of-business leaders to modernize analytics strategies</li> <li>Displace or expand legacy BI platforms with AI-powered, governed analytics solutions</li> <li>Lead conversations around semantic governance, self-service analytics, and natural language data access</li> <li>Drive proof-of-value engagements and scale enterprise-wide adoption</li> <li>Align AI/BI initiatives to measurable business outcomes (productivity, speed to insight, revenue impact)</li> <li>Enable field teams and serve as a subject matter expert on modern analytics architectures</li> </ul> <p data-renderer-start-pos="2367"><strong data-renderer-mark="true">What we look for:</strong></p> <ul> <li>Enterprise sales experience in BI, analytics, data platforms, or AI/ML</li> <li>Strong understanding of modern analytics architectures and data governance</li> <li>Ability to sell to both technical and business stakeholders</li> <li>Executive presence and experience navigating complex buying cycles</li> <li>Passion for AI and the impact of GenAI on enterprise analytics</li> <li>Experience operating in a specialist or overlay sales model</li> <li>Ability to translate technical capabilities into clear business value</li> <li data-renderer-start-pos="2386">7+ years of Enterprise Sales experience, exceeding quotas in larger accounts</li> <li data-renderer-start-pos="2386">Bachelors Degree or equivalent experience </li> </ul><div class="content-conclusion"><p><strong>About Databricks</strong></p> <p><span style="font-family: arial, sans-serif;">Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on <span style="color: rgb(255, 54, 33);"><a style="color: rgb(255, 54, 33);" href="https://twitter.com/databricks" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://twitter.com/databrickssource=gmailust=1700237575733000usg=AOvVaw03FL8fJvOD97ytN02f5G2C">Twitter</a>, <a style="color: rgb(255, 54, 33);" href="https://www.linkedin.com/company/databricks" target="_b ... (truncated, view full listing at source)