By Boluwatife Oshadiya | August 7, 2026
KEY POINTS
- Analysis of roughly 850,000 U.S. tech job postings between January 2025 and March 2026 shows hiring hit a three-year high even as layoffs surged
- Amazon Web Services (AWS) appeared in 30% of all postings, making cloud infrastructure — not AI hype — the single most demanded skill category
- Q1 2026 alone accounted for 39% of all postings in the dataset, representing 3.7 times more hiring activity than the same period a year earlier
- Nearly 42% of all postings required knowledge of at least one major cloud platform, confirming that the backbone of the internet remains the backbone of tech careers
- Tech, Data & Telecom companies posted 45% of all listings, with California, Texas, and New York leading geography
MAIN STORY
The American technology job market is in the middle of one of its most confusing chapters. Companies are cutting thousands of workers with one hand while posting record numbers of job listings with the other. Since January 2026, more than 170,000 tech jobs have been eliminated — roughly 832 per day — while venture capitalists poured $300 billion into AI startups in Q1 2026 alone. The question workers and analysts are asking is simple: what does a tech professional actually need to survive this moment?
A new report from Oxylabs, a web intelligence company based in Vilnius, Lithuania, offers the clearest data-driven answer yet. The firm analysed approximately 850,000 U.S. tech job postings published between January 2025 and March 2026, cross-referencing employer demand for specific technology tools, platforms, and skills. The findings puncture a number of widely held assumptions about what the market wants and reveal a hiring landscape shaped not by trending topics on social media, but by the unglamorous, load-bearing infrastructure skills that keep systems alive at scale.
The headline number is striking: Q1 2026 alone accounted for 39% of all postings in the dataset — 3.7 times more activity than Q1 2025. While company executives were justifying layoffs with AI efficiency narratives, their HR departments were simultaneously flooding job boards with a record volume of listings. The paradox is real, and it has a simple explanation: AI is not eliminating tech work. It is reorganising which tech work gets done by humans — and which humans get to do it.
The Oxylabs dataset, sourced from Coresignal’s multi-source jobs database, covered five major role categories — Software Engineering (38%), Data Science & AI/ML (14%), Tech & Engineering Management (14%), DevOps/Cloud/SRE (12%), and Data Analysis & BI (11%) — which together accounted for nearly 90% of all postings analysed. What emerged from that data is a hierarchy of skills that is at once familiar and instructive.
THE ISSUES
The most structurally significant finding from the Oxylabs research is not which tool ranked first — it is the distance between what trends online and what employers actually hire for. Cloud platforms and DevOps tooling together accounted for 77% of all tool mentions across the dataset. Meanwhile, the AI and machine learning tools that dominate conference keynotes and social media arguments appear as narrower, role-specific requirements rather than universal expectations.
This gap between hype and hiring reflects two underlying tensions. The first is the lag between industry narrative and employer behaviour: companies talk about AI transformation in press releases but continue to build systems on cloud infrastructure that requires experienced human management. The second is what might be called the infrastructure paradox — the more AI is deployed at scale, the more cloud infrastructure, DevOps tooling, and data engineering capacity is needed to run it. AI does not replace cloud skills; it deepens demand for them.
A separate tension exists in the geography of the market. California generates 13% of all postings, Texas 8%, and New York 5%. But Virginia — which does not appear in the top three on absolute volume — posts nearly three times as many tech jobs per capita as the national average, driven by the enormous concentration of data centres supporting the hyperscale cloud providers. The infrastructure economy is not just a technology story; it is a real estate, energy, and logistics story that is reshaping where tech talent actually needs to be.
For African tech professionals watching the U.S. market — whether as aspirants, diaspora workers, or talent competing in a globally distributed workforce — the data carries a clear message: the skills that cross borders most reliably are the same skills that dominate this dataset. Cloud certifications, DevOps tooling, and data engineering fluency travel well.
HERE ARE THE 10 MOST IN-DEMAND TECH SKILLS IN AMERICA RIGHT NOW — AND WHAT EACH ONE MEANS FOR YOUR CAREER
1. Amazon Web Services (AWS) — 30% of All Postings
AWS is not simply the most popular cloud platform. It is, by the data’s measure, the single most universally required technical skill in the American tech job market. Appearing in 30% of all 850,000 postings analysed, it outpaces the next closest competitor — Microsoft Azure — by approximately 1.2 times, and leads Google Cloud Platform by 2.1 times.
The dominance is not uniform across all roles. For Backend Engineers, AWS demand reaches 51% of postings. For DevOps and Site Reliability Engineers, the figure climbs to 58%. For Data Engineers, AWS appears in 47% of listings. Even Technology Managers — roles one might expect to be insulated from hands-on tool requirements — are expected to carry solid cloud familiarity.
AWS and Azure together appear in 15% of all postings, making multi-cloud literacy the single most valuable credential combination in the dataset. For anyone building a cloud career from scratch, AWS remains the non-negotiable starting point.
2. Microsoft Azure — 24% of All Postings
Azure’s 24% share of postings places it firmly in second position, but the more interesting story is geographic. While AWS leads in most U.S. states, Azure takes the top position in a cluster of Upper Midwest and Southern states — including Minnesota, Indiana, and Tennessee — likely driven by the heavy Microsoft 365 enterprise adoption in those regional economies.
For DevOps professionals, Azure appears in 45% of postings. For Data Engineers and Architects, the figure is 42%. The platform’s deep integration with Microsoft’s enterprise productivity stack — including Power BI and Excel, both of which appear elsewhere in this list — makes Azure fluency particularly valuable in Finance, Insurance, and Corporate IT environments.
The AWS-Azure gap is meaningful but not enormous. In practical terms, a professional who can work fluently across both platforms is positioned better than one who has committed exclusively to either.
3. Git — 21% of All Postings
Git’s position at number three on this list carries a specific message for early-career professionals: version control is not a beginner skill to learn and forget. It is a permanent, career-wide expectation. At 21% of all postings, Git outranks GCP, Kubernetes, Docker, and every business intelligence tool in the dataset.
Git’s universality cuts across role categories in a way few tools match. Software Engineers need it to manage codebases. Data Engineers use it to version pipeline code and configurations. ML practitioners use it to track model experiments. DevOps teams use it at the centre of CI/CD workflows. Git does not appear in this dataset as a specialised skill — it appears as a baseline competency, the professional equivalent of knowing how to type.
The practical implication is simple: if a tech professional does not have Git fluency, they are not fully functional in a modern engineering environment, regardless of their seniority or specialisation.
4. Microsoft Excel — 15% of All Postings
Excel’s presence at 15% of all postings — ahead of GCP, Kubernetes, and Docker — is one of the most counterintuitive findings in the entire report. In an era of cloud-native analytics platforms and modern BI tools, Excel remains a required skill across a substantial portion of the technical job market.
The Oxylabs report describes Excel as a “hygiene factor” — a baseline expectation that is so common in certain roles that its absence is disqualifying. In Data Entry and IT Support postings, Excel appears in 46% of listings. For Data Analysts and BI professionals, the figure is 41%.
The data also shows that Excel comfortably outpaces Google Sheets in employer demand. The Microsoft productivity ecosystem — Excel, Power BI, Azure — functions as an integrated suite in enterprise environments, and employers hiring for data-adjacent roles are not choosing between old tools and new ones. They are expecting both.
5. Google Cloud Platform (GCP) — 14% of All Postings
GCP’s 14% share places it third among the cloud platforms and tied with Kubernetes in the overall rankings. Its relative position — roughly half of AWS’s share and slightly below Azure’s — reflects the current state of the enterprise cloud market, where Google remains a strong third player with particular depth in data-intensive and AI-native applications.
For Data Engineers and Architects specifically, GCP appears in 24% of postings, making it more relevant to that role category than its overall ranking might suggest. The platform’s strengths in BigQuery, Dataflow, and Vertex AI align with data-heavy workloads, and its association with AI-native development gives it a specific niche in ML infrastructure hiring.
Regionally, GCP tends to cluster in California, driven by the concentration of tech firms and startups in the Bay Area where Google’s ecosystem has the deepest footprint.
6. Kubernetes — 14% of All Postings
Kubernetes and GCP are statistically tied at 14%, but they serve very different functions in the market. Where GCP is a cloud platform with broad application, Kubernetes is a container orchestration system that sits at the centre of modern DevOps and cloud-native application deployment.
For DevOps and SRE professionals — the role category with the highest overall infrastructure demand — Kubernetes appears in 39% of postings. The tool enables teams to manage containerised applications across multiple cloud environments, making it particularly valuable in multi-cloud and hybrid infrastructure setups.
Kubernetes’ position just ahead of Docker in this dataset is significant. The two tools are closely related — Docker creates containers, Kubernetes manages them at scale — and they frequently appear together in job descriptions. Kubernetes’ slight edge likely reflects the increasing expectation that DevOps professionals can move beyond building containers to orchestrating entire production environments.
7. Docker — 13% of All Postings
Docker appears in 13% of all postings, trailing Kubernetes by a single percentage point. The proximity is not coincidental. Docker and Kubernetes form what is arguably the most important two-tool combination in modern DevOps, and their near-equal demand reflects the reality that most employers hiring for infrastructure roles expect both.
Docker’s role in the stack is fundamental: it enables developers to package applications and their dependencies into portable, consistent containers that run identically across development, testing, and production environments. This portability is what makes cloud-native development possible at scale.
For professionals building a DevOps skill set, Docker is the logical entry point before advancing to Kubernetes. Understanding how containers are built before learning how they are orchestrated is both the pedagogically correct sequence and the career-relevant one.
8. Power BI — 9% of All Postings
Power BI’s 9% share of all postings, ahead of Tableau at 7.5%, reflects Microsoft’s growing dominance in the enterprise business intelligence market. The tool’s deep integration with the Microsoft 365 ecosystem — Excel, Azure, Teams — makes it the default BI platform in corporate environments where Microsoft is already the primary productivity vendor.
For Data Analysts and BI professionals, Power BI demand reaches 43% of postings, making it the single most required tool in that role category. The Oxylabs data suggests the market is settling into a Microsoft-first BI stack for enterprise data work, with Tableau remaining relevant in organisations with existing Salesforce relationships or legacy implementations.
The business intelligence category as a whole — covering Power BI, Tableau, and related tools — accounts for 18% of all tool mentions in the dataset, making it the third-largest tool category after Data Storage & Infrastructure (47%) and DevOps & Developer Experience (30%).
9. Terraform — 8% of All Postings
Terraform’s 8% share places it ninth overall, but its role concentration tells a more pointed story. Among DevOps and SRE professionals, Terraform appears in 38% of postings — a figure that reflects the tool’s position as the standard for Infrastructure as Code (IaC) in cloud environments.
Terraform, built by HashiCorp, allows engineers to define and provision cloud infrastructure through configuration files rather than manual console interactions. In environments where cloud resources are created and destroyed dynamically — and where reproducibility and auditability matter — IaC is not optional. It is operational standard.
The combination of Kubernetes (39%) and Terraform (38%) in DevOps postings illustrates the emerging baseline for senior infrastructure professionals: the ability to both orchestrate containerised workloads and define the cloud infrastructure those workloads run on, written as code, version-controlled, and deployable across environments.
10. Tableau — 7.5% of All Postings
Tableau rounds out the top ten at 7.5%, appearing in 36% of Data Analyst and BI-specific postings. While it trails Power BI in overall demand, Tableau retains strong relevance in organisations where its visualisation depth, flexibility, and Salesforce integration outweigh the convenience of Microsoft’s native ecosystem.
Tableau’s position in this dataset reflects a broader market reality: the business intelligence space is not winner-take-all. Power BI dominates the Microsoft-aligned enterprise, but Tableau holds ground in data-mature organisations with more complex visualisation requirements and analyst teams that prefer its interface and flexibility.
For BI professionals, dual fluency in Power BI and Tableau — alongside the Excel baseline — represents the most defensible skill profile in the current market.
WHAT’S BEING SAID
The research has landed in the middle of an industry-wide conversation about what AI actually means for tech employment, and the responses have been pointed.
Andrius Kūkšta, Tech Lead at Oxylabs, framed the findings directly: “The picture we saw after analyzing close to a million job postings largely confirms what experienced developers would guess — cloud, infrastructure, and data skills are in high demand. Where it gets more interesting is in the proportions: cloud platforms and DevOps tooling dominate job ads even more heavily than survey-based rankings suggest, while some high-visibility skills — the ones trending on X or headlining conference talks — appear less often than you might think.”
The observation about hype versus hiring demand aligns with a broader pattern analysts have documented across the industry. Workforce researchers have described what they are calling the “AI employment paradox” — the same companies eliminating tens of thousands of roles are simultaneously committing to the largest capital investment cycle in the industry’s history. Amazon Web Services, Microsoft Azure, Google Cloud, and Meta collectively plan to spend between $635 billion and $665 billion in 2026, a 67 to 74% increase over 2025, the overwhelming majority earmarked for AI data centres, chips, and infrastructure.
A study by The Pragmatic Engineer, which surveyed more than 900 engineers, found that while participants said they felt 20% more productive with AI tools, their actual demonstrated results showed a 20% decrease in productivity on average — a trust paradox that complicates the narrative companies are using to justify workforce reductions.
The human cost of that narrative is not abstract. According to outplacement firm Challenger, Gray & Christmas, AI was the most cited reason for tech layoffs through May 2026. Tech’s share of total U.S. layoff announcements has ballooned to nearly a third of all cuts — a concentration last seen during the post-pandemic correction of 2022-2023.
Yet the Oxylabs data suggests that even within this disruption, employers remain willing to invest in professionals with expertise in the infrastructure that actually runs the systems AI is supposed to be automating. The market is not contracting. It is reorganising — and the Oxylabs top 10 is, in effect, a map of where the demand is landing.
WHAT’S NEXT
- The Oxylabs dataset covers postings only through March 2026. Given that Q1 2026 already represented 3.7 times the activity of Q1 2025, subsequent quarterly data releases will indicate whether the hiring surge has sustained through Q2 and Q3 — or whether it represents a front-loaded burst of post-AI-investment demand.
- Goldman Sachs has forecast that sectors integrating AI strategically will create opportunities for reskilled professionals, particularly in data analysis, machine learning, and AI operations. The Q3 2026 hiring data will begin to show whether AI-adjacent roles are absorbing workers displaced from legacy tech positions.
- Virginia’s per-capita dominance in tech job postings — driven by data centre concentration — signals that infrastructure geography is shifting. Monitor state-level hiring data for indications that data centre expansion is creating distributed tech employment beyond the traditional California-Texas-New York corridor.
- The AWS Certified Security Specialty certification saw a 73% demand surge in one year, according to separate cloud hiring analysis, driven by AI systems creating new attack surfaces. Cybersecurity hiring data through the rest of 2026 will reveal whether that trend is sustained or front-loaded.
BOTTOM LINE
The Bottom Line: The American tech market’s headline paradox — mass layoffs running alongside record job postings — resolves cleanly when you look at what employers are actually hiring for. Cloud infrastructure, DevOps tooling, and foundational data skills are not collateral damage in the AI transition; they are the plumbing through which AI investment flows. The professionals most at risk are those whose roles existed primarily to manage organisational growth that has now slowed; the professionals most in demand are those who can keep systems running reliably at scale. For tech workers in Nigeria and across Africa who are building careers with one eye on the global market, the Oxylabs data offers a practical compass: AWS, cloud fluency, and infrastructure skills remain the most portable and most demanded credentials in the world’s largest tech economy — and that is unlikely to change while AI infrastructure spending continues its historic acceleration.
Sources: Oxylabs Research (July 2026); Challenger, Gray & Christmas; Layoffs.fyi; The Pragmatic Engineer; Goldman Sachs Research; TechCrunch; TechJournal; ThinkCloudly; Technerdo
