Data Engineer vs Data Scientist
Data Engineers and Data Scientists are the two most frequently confused roles in the data hiring market. Engineers build the infrastructure — pipelines, warehouses and data platforms. Scientists build models on top of that infrastructure — forecasting, classification and experimentation. Understanding where they overlap and where they diverge is useful whether you're hiring, switching tracks or mapping your next career move.
Data Engineer
932
open roles
Data Scientist
629
open roles
What the data shows
Data Engineer roles account for 60% of active listings between these two roles — 303 more open positions than Data Scientist right now.
Data Scientist commands a higher median salary — $118,588 vs $110,500 — a gap of roughly 7%. Both roles show meaningful upside at the 75th percentile.
Data Scientist skews more remote-friendly — 15% of listings offer remote work vs 13% for Data Engineer, a 2-point difference.
Data Scientist skews more senior — 47% of its listings target senior-level candidates, reflecting the depth of specialization the role demands.
Salary comparison
Data Engineer
P25
$73,758
Median
$110,500
P75
$150,314
Data Scientist
P25
$78,791
Median
$118,588
P75
$152,453
Salary estimates derived from active listings that include explicit pay ranges. Midpoint of stated range used to compute percentiles.
Shared skills
These skills appear in the top 12 for both roles — useful if you're considering a transition or working across both areas.
Data from active job listings · Updated hourly