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
IS WORK OVER?
Data engineer
31%
AI can already do 31% of this job.
#36 / 623
View rankingData 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.
| Task | Share | AI | Points |
|---|---|---|---|
Design pipelines, models and orchestration.EstimateNo public source provides a precise figure. This is our estimate. | 24% | 50% | +12 |
Write SQL, Spark and data tests.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 45% | +8.1 |
Incidents, quality and lineage in production.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Talk to analysts and negotiate data contracts.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 18% | +2.9 |
Cloud cost, permissions and PII.EstimateNo public source provides a precise figure. This is our estimate. | 14% | 15% | +2.1 |
Decide architecture and technical debt.EstimateNo public source provides a precise figure. This is our estimate. | 12% | 20% | +2.4 |
| Total | 100% | 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
IS WORK OVER?
Epidemiologist
31%
#34 / 623
View rankingEpidemiologist
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.
| Task | Share | AI | Points |
|---|---|---|---|
Surveillance, rates and the outbreak on the map.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 52% | +9.4 |
Studies, bias and the report for public health.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 48% | +7.7 |
Surveys, contacts and the case interview.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 28% | +4.5 |
Committee, the unpopular measure and the press.EstimateNo public source provides a precise figure. This is our estimate. | 18% | 18% | +3.2 |
Field, the care-home outbreak and dirty data.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 22% | +3.5 |
Judgement, uncertainty and signing the alert.EstimateNo public source provides a precise figure. This is our estimate. | 16% | 14% | +2.2 |
| Total | 100% | 31% |
Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low
Skills and activities
- watch outbreaks
- compute rates
- epi studies
- case interviews
- map epidemics
- public-health measures
- contact tracing
- health alerts
Sources for this job· O*NET 19-1041.00· ESCO/ISCO 2263