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Enterprise Account Executive, State and Local

Owns a geographic state and local government territory, originating and closing complex enterprise deals through regulated procurement processes and multi-stakeholder committees. Requires 5+ years of field sales experience, including 3+ years selling to state or local government accounts.

About the job

Responsibilities

  • Manage complex sales cycles and present to C-level executives.
  • Close net new accounts.
  • Identify and close quick, small wins while managing longer, complex sales cycles.
  • Exceed activity, pipeline, and revenue targets.
  • Track customer details—including use cases, purchase time frames, next steps, and forecasts—in Salesforce.
  • Use a solution-based approach to sell and create value for customers.
  • Promote the Databricks Data Intelligence Platform, leveraging Apache Spark, Delta Lake, and MLflow to drive data and AI transformation.
  • Prioritize strategic opportunities and apply appropriate opportunity strategies.

Requirements

  • Thrive in a fast-paced, high-growth environment and build greenfield public-sector territories.
  • 5+ years of field sales experience, including at least 3 years selling to state and/or local government accounts.
  • Demonstrated track record of closing deals in regulated procurement environments.
  • Ability to navigate multi-stakeholder buying committees and align competing priorities.
  • Strong executive presence and ability to engage credibly with commissioners, secretaries, CFOs, CIOs, and program leaders.
  • Strong track record of delivering measurable business value to customers.
  • Background in big data, cloud, AI/ML, or SaaS sales; ideally selling data and analytics platforms to government.
  • Bachelor's degree.

Compensation

  • ATS-listed pay range: $220,100–$302,600 USD.
  • Total compensation may also include an annual performance bonus, equity, benefits, and accelerators above 100% quota attainment.

Skills

Salesforce, Spark, Delta Lake, MLflow, Big Data, Cloud Computing, Artificial Intelligence, Machine Learning, SaaS, Data Analytics

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