Enterprise Geo Hunter Account Executive - Financial Services

SLSQ427R441

As an Enterprise Geo Hunter Account Executive at Databricks, you are a seasoned sales professional with experience selling to Financial Services 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 be asked to hunt after net new logos. Along with the chance to close an exciting deal, we also offer accelerators above 100% quota attainment.

The impact you will have:

• Meet with CIOs, IT executives, LOB executives, Program Managers, and other important partners
• Close both new accounts and existing accounts
• 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' enterprise cloud data platform powered by Apache Spark™
• 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:

• You have previously worked in an early stage company and you know how to navigate and be successful
• Field sales experience within big data, Cloud, or SaaS sales
• Prior customer relationships with CIOs, program managers, and essential decision makers
• Simply articulate intricate cloud technologies
• 4+ years experience exceeding sales quotas
• Expertise with financial services institutions preferable
• Success closing net new business
• Understanding of Spark and big data preferable
• Passion for cloud technologies
• Bachelor's Degree

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package