Data Engineer

What you'll do

• Build and run ingest pipelines for ERA5 (Copernicus), GFS/GEFS (NOAA) and ECMWF open data
• Design how forecast data is stored (Zarr on object storage) so it is cheap to keep and fast to read
• Handle GRIB2 decoding, partial or late model runs, and backfills without anyone babysitting them
• Bring NEXRAD radar into a near-real-time path for rain nowcasting

What we look for

• Production experience with large datasets and scheduled pipelines, where a silent failure is a real outage
• Python, object storage (S3 or similar), and a workflow scheduler such as Airflow or Prefect
• Experience with scientific formats (NetCDF, GRIB, Zarr) is a strong plus, but not required
• Instinct for where the cost sits — storage, compute and data transfer

How hiring works

1. Step 1

   Apply

   One page, about five minutes. Your LinkedIn and CV do most of the talking.

2. Step 2

   Verify your identity

   About three minutes: your phone, an ID document and a quick live selfie, run by Didit. Every candidate does this before an interview.

3. Step 3

   Book a 15-minute call

   Once you're verified, we email you a link to pick a time — weekdays, 8am–4pm Eastern Time (ET), at least 24 hours ahead. We read your application before we talk.

4. Step 4

   Talk and agree terms

   The intro call, a technical conversation about work you've actually done, then contract terms, rate and start date in writing.

Pay

$65 – $100 per hour as an independent contractor, depending on experience. We publish the range on every role so you know before you apply, not after three interviews.

About Ensemble Weather AI

We combine many independent AI weather models into one better-calibrated forecast and deliver it as an API — severe storms, nowcasting, air quality and long-range climate. It's early: the ingest pipelines, the ensembling layer and the v1 API are being built now, so the people who join next will own that core rather than maintain someone else's.