AWS Jobs Ask for Azure More Often Than They Ask for Kubernetes.
Based on 231,147+ analyzed job listings · Updated 2026-07-21
The assumed path after AWS is containers: learn Kubernetes, then Terraform, then go deeper on infrastructure. We measured what employers actually pair with AWS across 19,015 engineering postings that require it, and the top two are not containers at all. Azure appears in 41.1% of AWS postings and Google Cloud in 36.7%. Kubernetes is fourth at 29.5%. Employers hiring for AWS are, more often than not, hiring for someone who can work across more than one cloud.
19,015
AWS postings analyzed
Active engineering listings that require AWS, out of 76,436 engineering postings
41.1%
Also want Azure
2.9x the rate across engineering as a whole
36.7%
Also want Google Cloud
2.8x the engineering baseline
29.5%
Also want Kubernetes
Fourth, behind both rival clouds and CI/CD
What AWS postings also require
| Also required | Share of AWS postings | Lift vs. engineering |
|---|---|---|
| Azure | 41.1% | 2.9x |
| Google Cloud | 36.7% | 2.8x |
| CI/CD | 33.4% | 2.0x |
| Kubernetes | 29.5% | 2.5x |
| Docker | 25.3% | 2.5x |
| DevOps practice | 25.1% | 2.0x |
Share is the percentage of the 19,015 AWS postings that also require each skill. Lift is how much more often it appears in AWS postings than across all 76,436 engineering postings, which filters out skills that are simply common everywhere.
Source: Seeker job corpus, 231,147 active job postings, snapshot 2026-07-21. seekerscore.com/insights/aws-second-cloud-2026
The ranking is not what the discourse suggests
Among postings that require AWS, Azure appears in 41.1% and Google Cloud in 36.7%. Kubernetes appears in 29.5%, Docker in 25.3%. The gap between the second cloud and the container orchestrator is 11.6 percentage points, which is not a rounding difference. Lift tells the same story from the other direction: Azure is 2.9x more common in AWS postings than in engineering generally, Google Cloud 2.8x. These are not skills that happen to be popular everywhere and show up here by coincidence. They are specifically co-required with AWS.
Why employers ask for two clouds
We measured what postings say, not why they say it, so this part is inference rather than measurement and should be read that way. The most likely explanation is that organizations large enough to write an infrastructure job description are rarely on one cloud. They have an acquisition running elsewhere, a data platform on a different provider, a compliance requirement pushing a workload somewhere specific, or a negotiating position they want to keep. The person they are hiring is expected to operate across that, not to specialize deeper into one vendor. Kubernetes is portable across all of them, which may be exactly why it is not the differentiator: it is assumed rather than requested.
What to do with this
If you have AWS and are choosing what to add, the corpus says a working knowledge of a second cloud opens more postings than going deeper on orchestration. Azure first by volume, Google Cloud close behind. That is a different investment from the usual advice: not another layer on the same stack, but the same layer on a different provider. The caveat worth stating is that this measures which postings you become eligible for, not which ones you win. A posting that names three clouds is not asking for expert depth in all three, and claiming it would be worse than not listing it.
How we measured it (and what we did not claim)
We took the 19,015 active engineering postings whose extracted skills include AWS, out of 76,436 engineering postings total, and counted how often each other skill appears alongside it. Ranking is by lift, meaning how much more often a skill appears in AWS postings than across engineering as a whole, with a minimum volume floor so the list cannot be topped by a skill that appears in a handful of postings at high multiples. Skills come from our extraction pipeline rather than from a hand-read of each posting, so a skill the employer implied but did not name is not counted, and every figure is a floor. The lift ranking is doing real work here: without it, generic terms that appear on nearly every posting would dominate the list and tell you nothing. This measures co-occurrence in job postings, not what engineers actually use day to day, and not what gets someone hired.
Frequently asked questions
What should I learn after AWS?
Measured across 19,015 AWS postings, the most commonly co-required skills are Azure at 41.1% and Google Cloud at 36.7%, both ahead of Kubernetes at 29.5%. If the goal is to be eligible for more postings, a second cloud opens more doors than deeper container work.
Is Kubernetes still worth learning?
Yes, but it is not the differentiator in AWS roles that many assume. It appears in 29.5% of AWS postings, which is substantial, but it ranks behind Azure, Google Cloud and CI/CD. One plausible reading is that Kubernetes is portable across every cloud and therefore assumed rather than requested, though the postings themselves do not say that.
Do employers really want people who know multiple clouds?
In this corpus, yes. Azure appears in 41.1% of AWS postings at 2.9x the engineering baseline, and Google Cloud in 36.7% at 2.8x. The lift figures matter: these are not skills that are simply common everywhere, they are specifically co-required with AWS.
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Guides
Data derived from Seeker's job corpus of 231,147+ listings across multiple sources. Updated 2026-07-21. Individual results vary based on resume content, target market, and role specifics.