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Emerging Enterprise Account Executive

Databricks · 30+ days ago
Negotiable
Full-time
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SLSQ126R20

As an Emerging Enterprise Account Executive at Databricks, you are a sales professional experienced in selling remotely to large and medium-size accounts. You know how to sell innovation and change through customer vision expansion and can guide deals forward to compress decision cycles. You love understanding a product in depth and are passionate about communicating its value to Customers and System Integrators. Always looking for new opportunities, you will work with a large volume of scaling accounts. Along with the chance to close a large volume of exciting deals, we also offer accelerators above 100% quota attainment.

You will report to the Sales Director.

The impact you will have:

  • Connect with IT executives, LOB executives, Program Managers and partners
  • Identify and close quick, small wins while managing longer, complex sales cycles
  • Exceed activity, pipeline, and revenue targets
  • Track all customer details including use case, purchase time frames, next steps, and forecasting in Salesforce
  • Use a solution-based approach to selling and creating value for customers
  • Promote Databricks' Data Intelligence Platform and other core solutions such as Datalakehouse. 
  • Ensure 100% satisfaction among all customers
  • Prioritize opportunities and applying appropriate resources
  • Build a plan for success internally at Databricks and externally with your accounts.

What we look for:

  • Fluent proficiency in Spanish, professional-level fluency in English. Portuguese fluency is nice to have but not required.
  • You have previously worked in an early stage company and you know how to navigate and be successful
  • Sales experience within Cloud, or SaaS sales
  • Prior customer relationships with CIOs, program managers, and essential decision makers
  • Simply articulate the value of data and Gen AI technologies to different industries
  • 3+ years experience exceeding sales quotas in a full-cycle closing role
  • Success working in high growth, scaling accounts
  • Understanding of Apache Spark™ and big data preferable
  • Bachelor's Degree

Benefits:

  • Comprehensive health coverage including: medical, dental, and vision
  • Equity awards
  • Flexible time off
  • Paid parental leave
  • Family Planning
  • Gym reimbursement
  • Annual personal development fund
  • Work headphones reimbursement
  • Employee Assistance Program (EAP)
  • Business travel accident insurance

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 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 TwitterLinkedIn and Facebook.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Last updated on Aug 19, 2024

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About the company

D
DatabricksDatabricks provides a data and AI platform for businesses, offering data engineering, data science, and machine learning tools and services.

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