IS WORK OVER?

Automation index

How much of a Data engineer’s job can AI already do?

A pipeline and a diagram sketch. Keeping it up at 3 a.m., with PII and a four-hour job, does not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Data engineer

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Design pipelines, models and orchestration.
Estimate

No public source provides a precise figure. This is our estimate.

24%50%+12
Write SQL, Spark and data tests.
Estimate

No public source provides a precise figure. This is our estimate.

18%45%+8.1
Incidents, quality and lineage in production.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Talk to analysts and negotiate data contracts.
Estimate

No public source provides a precise figure. This is our estimate.

16%18%+2.9
Cloud cost, permissions and PII.
Estimate

No public source provides a precise figure. This is our estimate.

14%15%+2.1
Decide architecture and technical debt.
Estimate

No public source provides a precise figure. This is our estimate.

12%20%+2.4
Total100%31%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • Design pipelines, models and orchestration
  • Write SQL, Spark and data tests
  • Cloud cost, permissions and PII
  • Decide architecture and technical debt
  • ingeniero de datos
  • data engineer
  • etl

Sources for this job· O*NET 15-1243.00· ESCO/ISCO 2511

Ice-cream maker

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Base, overrun and the recipe.
Estimate

No public source provides a precise figure. This is our estimate.

16%44%+7
Churn, age and the one that crystals.
Estimate

No public source provides a precise figure. This is our estimate.

18%12%+2.2
List, season and the flavour that misses.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
Workshop, cold and the broken chain.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Summer, the queue and not running out of vanilla.
Estimate

No public source provides a precise figure. This is our estimate.

18%18%+3.2
Creamy in the mouth, and not selling ice.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%22%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • churn
  • overrun
  • age bases
  • ice-cream list
  • cold chain
  • ice crystals
  • vanilla
  • ice-cream season

Sources for this job· O*NET 51-3099.00· ESCO/ISCO 7512

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