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Databricks

Builds cloud software for data analysis and AI

Lakebase Sales Specialist Account Executive

Account ExecutiveConfirmed live in the last 24 hours
Full-timeSingaporeNo salary listed

About the Job

Requirements

  • Have 7 or more years of enterprise software-as-a-service sales experience, consistently exceeding quota in complex, multi-stakeholder deals in the Greater China region.
  • Demonstrate success selling data platforms, operational databases such as Postgres, MySQL, or cloud-native database-as-a-service offerings, or adjacent data and artificial intelligence infrastructure to technical buyers and business leaders.
  • Understand modern data and application architectures, including cloud-native services, microservices, event-driven systems, and the role of operational data in artificial intelligence and analytics strategies.
  • Be able to sell to technical stakeholders, including developers, architects, and data engineers, as well as business stakeholders, including product leaders, operations, and line-of-business owners.
  • Have experience leading specialist or overlay sales motions and working jointly with core Account Executives to create and progress opportunities.
  • Demonstrate executive presence, including the ability to whiteboard architectures, lead C-level conversations, and build trust with senior decision-makers.
  • Demonstrate value-selling skills, including discovering customer pain, building a business case, and connecting technical capabilities to clear, quantified outcomes.
  • Have communication, storytelling, and negotiation skills, and be comfortable presenting to large and small audiences.
  • Have a bachelor's degree or equivalent practical experience.
  • Have business proficiency in Mandarin and experience in the Greater China region; engage customers in Mandarin for technical and business discussions, addressing sales challenges, and presenting value propositions and outcomes.

Responsibilities

  • Drive new Lakebase revenue by identifying, qualifying, and closing Lakebase opportunities in a defined territory, in partnership with regional Account Executives and the broader account team.
  • Lead with outcomes for platform teams and developers, data teams, and central IT by explaining how Lakebase helps customers ship features faster, simplify operational data architectures, and improve governance and cost efficiency.
  • Sell the value of fully managed Postgres for intelligent applications, positioning Lakebase for operational workloads that power real-time, artificial-intelligence-driven experiences.
  • Run complex, multi-threaded sales cycles from discovery and value hypothesis through commercial negotiation and close, engaging executive, technical, and line-of-business stakeholders.
  • Orchestrate proof-of-value engagements and proofs of concept to validate Lakebase benefits for online transaction processing-style workloads, reverse extract-transform-load, and artificial-intelligence- and machine-learning-driven applications, in partnership with solution architects and specialists.
  • Compete against legacy and cloud-native operational databases by using competitive assets, benchmarks, and customer references.
  • Align sales activity to measurable business outcomes, including performance, developer productivity, time-to-market for new features, cost reduction, and simplification of operational data environments.
  • Partner with Product Management, Marketing, Customer Success, and Partner teams to shape territory plans, launch plays, and co-selling motions with key independent software vendors and global systems integrators.
  • Enable the field by sharing Lakebase best practices, success stories, and sales motions with broader sales teams to scale Lakebase proficiency across the organization.
  • Establish top strategic focus accounts by engaging application development teams to create new intelligent applications using Lakebase.
  • Drive longer-term Postgres standardization and migration within Databricks' most strategic accounts.
  • Track revenue, pipeline, and key observations at a business-unit level, and identify areas requiring additional focus or support.
  • Partner with account teams to engage priority accounts across the global DB700 and drive strategic opportunities from initial engagement through successful outcomes.
  • Build and execute enablement plans that empower Account Executives and Solution Architects to confidently carry the Lakebase conversation when the specialist is not present.
  • Develop an internal and external presence by contributing to global ask-me-anything sessions and internal forums, and represent Databricks at key first- and third-party events.

Desired Qualifications

  • Have experience selling Postgres, operational databases, online transaction processing workloads, or transactional cloud database services, ideally within large or strategic accounts.
  • Be familiar with data platforms, lakehouse architectures, and cloud ecosystems such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform, including the role of operational databases in broader data and artificial intelligence strategies.
  • Understand reverse extract-transform-load, real-time decisioning, and operational analytics use cases and how they create value for customer-facing and internal applications.
  • Have exposure to artificial-intelligence-native and agent-driven applications that depend on low-latency, highly scalable operational data services.
  • Have prior experience in a high-growth, category-creating environment, helping shape new sales plays, messaging, and customer narratives.
  • Have experience collaborating with partners and independent software vendors to drive joint pipeline and co-selling motions.

About the Company

Databricks

Builds cloud software for data analysis and AI

Databricks builds cloud software that businesses use to organize data, analyze it, and develop AI applications. Its lakehouse architecture brings the flexible storage of a data lake together with the querying and management tools of a data warehouse. Data engineers prepare and update datasets, analysts build reports, and developers train models or create applications in a shared workspace with controls over who can use the data. The platform runs on Amazon, Microsoft, and Google clouds, and customers pay for computing usage or commit to longer contracts for discounted rates. Databricks was founded in 2013 and is headquartered in San Francisco, California.

Company size
10,001+
Company stage
Late Stage VC
Total funding
$32.1B
Headquarters
San Francisco, CA
Founded
2013

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