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Databricks

Lakebase Sales Specialist

Milan, Italy
Company's own boardBachelor's degree

First seen Aug 4 · seen live today · from Databricks's own Greenhouse board

Skills mentioned

gopostgresmysqlawsazuregcpproduct management

The posting, as published

<p data-pm-slice="1 1 []">SLSQ327R364</p> <p>Databricks is seeking a&nbsp;<strong>Lakebase Sales Specialist&nbsp;</strong>to help customers modernize their operational data foundation with&nbsp;<strong>Databricks Lakebase</strong>, our&nbsp;<strong>fully-managed Postgres</strong>&nbsp;offering for&nbsp;<strong>intelligent applications</strong>. This high-impact role sits within the Lakebase Go-To-Market team and partners closely with regional Account Executives to drive adoption of Lakebase with platform, application, and data teams.</p> <p>Lakebase gives customers a unified, governed foundation for&nbsp;<strong>operational workloads</strong>&nbsp;and&nbsp;<strong>AI-native applications</strong>, helping them move away from a fragmented estate of point databases toward a modern, scalable, serverless Postgres service. If you want to be at the forefront of operational databases for AI and intelligent applications at one of the fastest-growing data and AI companies in the world, this is your opportunity.</p> <h2><strong>The impact you will have</strong></h2> <ul> <li><strong>Drive new Lakebase revenue</strong>&nbsp;by identifying, qualifying, and driving Lakebase activations and consumption within a defined territory, in partnership with regional Account Executives and the broader account team.</li> <li><strong>Lead with outcomes</strong>&nbsp;for key Lakebase personas — including&nbsp;<strong>platform teams and developers</strong>,&nbsp;<strong>data teams</strong>, and&nbsp;<strong>central IT</strong>&nbsp;— articulating how Lakebase helps them ship features faster, simplify operational data architectures, and improve governance and cost efficiency.</li> <li><strong>Sell the value of fully-managed Postgres for intelligent applications</strong>, positioning Lakebase as the optimal choice for operational workloads that power real-time, AI-driven experiences.</li> <li><strong>Run complex, multi-threaded sales cycles</strong>&nbsp;from discovery and value hypothesis through commercial negotiation and close, navigating executive, technical, and line-of-business stakeholders.</li> <li><strong>Orchestrate proof-of-value and POCs</strong>&nbsp;that validate Lakebase’s benefits for OLTP-style workloads, reverse ETL, and AI/ML-driven applications, in partnership with solution architects and specialists.</li> <li><strong>Compete and win</strong>&nbsp;against legacy and cloud-native operational databases by leveraging our compete assets, benchmarks, and customer references.</li> <li><strong>Align to measurable business outcomes</strong>&nbsp;such as performance, developer productivity, time-to-market for new features, cost reduction, and simplification of the operational data landscape.</li> <li><strong>Partner cross-functionally</strong>&nbsp;with Product Management, Marketing, Customer Success, and Partner teams to shape territory plans, launch plays, and co-selling motions with key ISVs and GSIs.</li> <li><strong>Enable the field</strong>&nbsp;by sharing Lakebase best practices, success stories, and sales motions with broader sales teams, helping scale Lakebase proficiency across the organization.</li> </ul> <h2><strong>What success looks like in this role</strong></h2> <p>This role requires the ability to operate across&nbsp;<strong>two key motions</strong>&nbsp;simultaneously:</p> <ul> <li><strong>Establish top strategic focus accounts</strong>&nbsp;by engaging application development teams to create net-new intelligent applications leveraging Lakebase.</li> <li><strong>Drive longer-term Postgres standardization and migration</strong>&nbsp;within Databricks' most strategic accounts.</li> </ul> <p>Candidates should demonstrate how they can&nbsp;<strong>act as a force multiplier</strong>&nbsp;across multiple dimensions of the business.</p> <p>Success in this role requires strength in four areas:</p> <ol> <li><strong>Business ownership</strong>&nbsp;– Operate at a business-unit level by tracking revenue, pipeline, and key observations, and by identifying areas needing additional focus or support.</li> <li><strong>Strategic account engagement</strong>&nbsp;– Partner with account teams to engage priority accounts across the global DB700, driving strategic opportunities from initial engagement through successful outcomes.</li> <li><strong>Field, account, &amp; customer enablement:&nbsp;</strong>Align customers and the field on the value of Lakebase by equipping AEs and SAs with the messaging and execution motions needed to confidently own accounts without specialist intervention.</li> <li><strong>Market voice and thought leadership</strong>&nbsp;– Develop an internal and external presence by contributing to global AMAs and internal forums, and by representing Databricks at key first- and third-party events.</li> </ol> <p>The interview process is designed to evaluate candidates across all four of these dimensions.</p> <h2><strong>What we look for</strong></h2> <ul> <li><strong>Proven enterprise SaaS sales experience</strong>, consistently exceeding quota in complex, multi-stakeholder deals.</li> <li>Proven success selling&nbsp;<strong>data platforms, operational databases (e.g., Postgres, MySQL, cloud-native DBaaS), or adjacent data/AI infrastructure</strong>&nbsp;to technical buyers and business leaders.</li> <li>Strong understanding of&nbsp;<strong>modern data and application architectures</strong>, including cloud-native services, microservices, event-driven systems, and how operational data underpins AI and analytics strategies.</li> <li>Ability to sell to both&nbsp;<strong>technical stakeholders</strong>&nbsp;(developers, architects, data engineers) and&nbsp;<strong>business stakeholders</strong>&nbsp;(product leaders, operations, line-of-business owners).</li> <li>Demonstrated experience leading&nbsp;<strong>specialist or overlay motions</strong>, working jointly with core Account Executives to create and progress opportunities.</li> <li>Executive presence with the ability to&nbsp;<strong>whiteboard architectures</strong>, lead C-level conversations, and build trust with senior decision makers.</li> <li>Strong&nbsp;<strong>value selling</strong>&nbsp;skills: adept at discovering pain, building a business case, and tying technical capabilities to clear, quantified outcomes.</li> <li>Excellent&nbsp;<strong>communication, storytelling, and negotiation</strong>&nbsp;skills, with comfort presenting to both large and small audiences.</li> <li>Bachelor’s degree or equivalent practical experience.</li> <li>Fluency in English and in Italian required.</li> </ul> <h2><strong>Preferred qualifications</strong></h2> <ul> <li>Experience selling&nbsp;<strong>Postgres, operational databases, OLTP workloads, or transactional cloud database services</strong>, ideally within large or strategic accounts.</li> <li>Familiarity with&nbsp;<strong>data platforms, lakehouse architectures, and cloud ecosystems</strong>&nbsp;(AWS, Azure, GCP), including how operational databases fit within broader data and AI strategies.</li> <li>Understanding of&nbsp;<strong>reverse ETL, real-time decisioning, and operational analytics</strong>&nbsp;use cases, and how they drive value for customer-facing and internal applications.</li> <li>Exposure to&nbsp;<strong>AI-native and agent-driven applications</strong>&nbsp;that depend on low-latency, highly scalable operational data services.</li> <li>Prior experience in a&nbsp;<strong>high-growth, category-creating environment</strong>, helping shape new plays, messaging, and customer narratives.</li> <li>Experience collaborating with&nbsp;<strong>partners and ISVs</strong>&nbsp;to drive joint pipeline and co-sell motions.</li> </ul> <p><em>This description is intended to outline the core responsibilities and qualifications for the Lakebase Sales Specialist role. Actual responsibilities may evolve as the Lakebase product and go-to-market motions continue to grow and mature.</em></p> <div class="content-conclusion">&nbsp;</div> <p data-renderer-start-pos="27

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