Hire AWS data engineers who can run the platform

An AWS data engineer owns how data lands in your account and how other teams read it. That usually means S3 for files, Glue or Spark for transforms, Redshift or Athena for queries, and IAM that does not hand the whole account to one job.

Day to day they own:

• Landing. Files and streams arrive in the right bucket, with a name and a schema you can explain.
• Transforms. Glue, EMR, or a container job turns that into tables.
• Access. Analysts and services can read what they should, and nothing else.

Certifications are a signal. A clear story of a pipeline they ran in an account you could audit is the better one.

You probably need this hire when:

• Your data is already in AWS and nobody owns the buckets, the jobs, or the cost.
• You are leaving a server in a closet for S3 and a warehouse.
• IAM and networking are slowing every new source.
• A product feature needs data from your account, on a schedule.

If the same work sits in Microsoft Fabric, see Azure data engineers. If the lakehouse is Databricks, see Databricks talent.

Account hygiene. They can draw the path from a source to a table, name the role the job assumes, and say what happens when a file is late.

Cost in plain language. They know which scans are expensive and which storage class fits the data you actually reread.

More than the console. Jobs live in code. A click-path that nobody else can repeat is a warning sign.

What to ask

• How do you partition a large S3 dataset, and what did you change after the first month of bills?
• Walk through the IAM a Glue job needs, and what you refuse to grant.
• When would you choose Athena over Redshift for this question?

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.