Databricks

Databricks

Sr. Solutions Architect - Public Sector (SLED)

Remote - California · Senior

Sponsorship not specified$219k-$301kDetected 23 hours ago
PythonJavaScalaSQLDatabricksAWSGCPAzureCloud PlatformsKafkaMachine LearningSparkData AnalysisData EngineeringData ScienceSalesResearchLeadershipHadoop

About the role

  • As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science and machine learning.
  • You will report to the Field Engineering Manager for the team.
  • The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.

Requirements

  • [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)

Skills

  • Experience supporting Public Sector clients

Compensation

  • Databricks is committed to fair and equitable compensation practices.
  • The pay range(s) for this role is listed below and represents the expected 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.
  • The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.
  • Local Pay Range
  • $219,100 - $301,300 USD

Benefits

  • At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.
  • For specific details on the benefits offered in your region click here.

Company info

  • At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel.

Equal opportunity

  • Our Commitment to Diversity and Inclusion

Visa & Work Authorization

  • US Citizen
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This listing is sourced directly from Databricks's careers page and normalized into a canonical job model.