Candidate Experience Admin (6-month contract)

Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.

Series F+0 current maintainers0 active leads
160 Spear Street, Suite 1300, San Francisco, CA 94105, United States
About Databricks

Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.

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Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will be the primary onsite point of contact for candidates visiting our offices, keeping communication timely, professional and friendly. You will manage physical logistics on the day, greet candidates, handle room changes and troubleshoot live. You will also coordinate time-sensitive interviews and contribute to data-driven improvements of the candidate experience.

Requirements

  • Hands-on logistics management and real-time troubleshooting
  • Effective communication and prioritization skills
  • Ability to thrive in a fast-paced environment
  • Collaborative mindset and openness to feedback
  • Proactive approach to resolving ambiguous challenges
  • High accuracy and attention to detail
  • Interest in technology and artificial intelligence
  • In person in San Francisco or Mountain View office 5 days a week

Responsibilities

  • Serve as the primary onsite point of contact for candidates
  • Manage timely, professional and friendly written and verbal communication
  • Build relationships with the Talent Acquisition team and hiring stakeholders
  • Manage physical logistics, candidate greetings, room changes and live troubleshooting
  • Coordinate interviews and time-sensitive scheduling
  • Identify data-driven improvements and ad hoc projects for recruitment processes