Account Executive, Singapore
crypto:applicationbusinessIC4Enterprise Sales
Compensation
Not disclosed
As we continue to increase our presence in the world of Unified Data Analytics and AI, we're looking for a creative, driven, and execution-oriented Enterprise Account Executive to sell and maximize the huge market opportunity that exists for Databricks today. As an Enterprise Account Executive reporting to the Regional Sales Director, you will have experience selling in the Enterprise segment. Your informed point of view on Big Data and Advanced Analytics will guide your successful sales strategy together with our teams and partners, allowing you to provide value to our biggest and most valued customers.
The impact you will have:
Evangelize Databricks' Unified Analytics Platform powered by Spark and launch the Databricks brand in Enterprise Accounts across all industries
Prospect, identify and source new sales opportunities, building pipeline individually and with the Databricks SDR team
Engage with business and technical decision-makers and lead them through the evaluation and buying process
Exceed individual activity, pipeline, and annual revenue targets
Engage with and drive business through local partners (technology partners, ISVs, SIs, and GSIs)
Drive customer success and upsell existing customers
Create a Territory Strategy across all industries
What we look for:
5+ years of experience selling SaaS solutions to Enterprise customers in ASEAN region
Proven success in Enterprise Sales roles, ideally in big data, Cloud, or SaaS technology
Demonstrable experience in selling innovation, ideally in big data, Cloud, or SaaS technology
Solution and business-outcomes-focused sales approach (Command of the Message, MEDDPIC, Challenger Sale)
Ability to simply articulate intricate cloud & big data technologies and their business value for the customer
About Databricks
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 In