Hire a data engineer in the United States

A data engineer builds and runs the pipelines that move data from your apps and tools into a warehouse or lake, on time and in a shape people can use. In US teams that usually means a cloud warehouse such as Snowflake, BigQuery, Redshift, or Databricks, with dbt or Spark on top.

Day to day they own ingestion, transformation, and the tables that dashboards and models read. See Hire data engineers for the full role.

The mainland United States spans Eastern, Central, Mountain, and Pacific time. A data engineer on Pacific time shares the East Coast afternoon, not its morning. Decide which hours matter, then set them on the role.

If US hours matter more than a US address, widen the location and keep the overlap hours. Data engineers across the Americas can cover them. See hiring for Americas hours.

• Employee through your US entity. You run payroll and register in the state where the person works. Rules on leave and final pay differ by state.
• Independent contractor. Federal and state tests decide whether the person is a contractor or an employee. Some states are stricter than others. Check the rules for their state before you choose.
• No US entity. Use an employer of record. Carbon's EOR partner is Deel. See hiring internationally.

carbon.talent does not employ the person. You agree the terms with them.

There is no single federal privacy law in the United States. State laws, such as California's CCPA as amended by the CPRA, apply alongside sector rules such as HIPAA for health data and GLBA for financial data. A data engineer touches all of it.

Ask how they keep personal data out of places it should not be: masking, access by role, and a way to delete a person's records across every table.

• Walk through a pipeline you own. What happens when a source is late?
• How do you backfill a table without doubling rows?
• Where does personal data live in your current warehouse, and who can read it?
• Which US hours can you overlap with our team, every week?

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 the United States as the country, or set US 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.