Hire Databricks talent who run the lakehouse

A Databricks hire owns the lakehouse. They turn notebooks into jobs other people can rerun, keep Delta tables with a grain you can explain, and set compute so a Monday dashboard does not surprise you.

Day to day they own:

• Tables. How data lands, how it updates, and what one row means.
• Jobs. A schedule, a failure you can see, and a backfill that is safe to repeat.
• Access. Workspaces and catalogs that match the teams who should read the data.

Analytics and machine learning often share this platform. Say on the role which of those is the job for the first ninety days.

You probably need this hire when:

• Important logic still lives in a notebook on one laptop.
• You are moving warehouse work onto Databricks and need an owner.
• Jobs fail quietly and the downstream report is stale.
• Analysts and model work share the platform, and nobody owns the tables.

If the product is a language-model feature, see AI engineers. If you need a classical model in production, see machine learning engineers. If the cloud account around Databricks is the gap, see AWS or Azure.

Jobs, not hero notebooks. A teammate can rerun yesterday without the original author.

Tables with a grain. They can defend one important table: what changed, how often, and who uses it.

A calm compute story. They can say which job moved the bill and what they changed.

What to ask

• Walk through a Databricks job you shipped. What happens when it fails halfway?
• How do you backfill a table without doubling rows?
• Who can read the catalog, and how is that decision reviewed?

carbon.talent is a data and AI talent platform. Post a role, see who applied, and hire.

1. Post a role. Title, stack, seniority, and whether you want permanent, contract, or fractional. Set remote or on-site, the country, and the overlap hours.
2. See who applied. Open each profile. Review a real-world data experience test, a working-style profile, and a video interview when they are on the profile.
3. Hire. Interview, agree the terms with the person, and hire on the platform. ID checks are on Team and Scale.

Already found someone? Test a candidate you found, then decide.

Companies post this role from anywhere. You choose where the person is based and which hours they overlap with your team.

Remote, hybrid, and on-site use the same flow. Location is a setting on the role.