Skills in 200+ New Zealand tech job postings: the data
We analysed 209 New Zealand tech job postings saved between August–October 2026, counting how often each of 68 skill terms appears. This is a convenience sample, not a random one — read the method and limitations before citing it.
Key findings
- Of the 68 terms tracked, the most common was Communication — it appeared in 43.5% of the postings we analysed.
- The most common technical skill was CI/CD at 34.5% of postings.
- 52 of the 68 tracked terms are technical skills — the other 16 are practices and soft skills, and in this sample they outrank most of the stack.
- AI was the largest role family in the sample, with 81 of 209 postings.
Top tech skills in the postings
Languages, frameworks, cloud and data tooling — the 52 technical terms we track, ranked by how many of the 209 postings mention them.
| Skill | Category | Postings | % of postings |
|---|---|---|---|
| CI/CD | Cloud | 72 | 34.5% |
| AWS | Cloud | 68 | 32.5% |
| Python | Language | 63 | 30.1% |
| Azure | Cloud | 55 | 26.3% |
| DevOps | Cloud | 53 | 25.4% |
| AI agents | AI | 45 | 21.5% |
| LLMs | AI | 39 | 18.7% |
| SQL | Language | 37 | 17.7% |
| TypeScript | Language | 36 | 17.2% |
| React | Frontend | 35 | 16.7% |
| Java | Language | 32 | 15.3% |
| Machine learning | AI | 26 | 12.4% |
| .NET | Backend | 25 | 12.0% |
| Kubernetes | Cloud | 24 | 11.5% |
| C# | Language | 23 | 11.0% |
Top practice and soft-skill terms
Working practices and soft skills, ranked the same way. In this sample they appear more often than most technologies. Several are matched by broad phrases (“security” counts any mention), so read them as how often a posting raises the topic, not as a hard requirement.
| Term | Category | Postings | % of postings |
|---|---|---|---|
| Communication | Soft skill | 91 | 43.5% |
| Teamwork | Soft skill | 84 | 40.2% |
| Security | Practice | 80 | 38.3% |
| Leadership | Soft skill | 73 | 34.9% |
| Mentoring | Soft skill | 60 | 28.7% |
| Agile | Practice | 41 | 19.6% |
| Problem solving | Soft skill | 39 | 18.7% |
| Code review | Practice | 38 | 18.2% |
| Cross-functional | Soft skill | 33 | 15.8% |
| Test automation | Practice | 32 | 15.3% |
By role family
The same terms, split by the role family they appeared in. Percentages are of that family's postings; a dash means the term showed up in too few of them to report.
AI
81 NZ postings in this family
| Term | % of family postings |
|---|---|
| AI agents | 44.4% |
| Communication | 44.4% |
| LLMs | 39.5% |
| Python | 39.5% |
| AWS | 38.3% |
| Security | 38.3% |
| Teamwork | 38.3% |
| Leadership | 35.8% |
Backend
58 NZ postings in this family
| Term | % of family postings |
|---|---|
| Security | 51.7% |
| CI/CD | 48.3% |
| AWS | 43.1% |
| DevOps | 43.1% |
| Teamwork | 39.7% |
| Communication | 36.2% |
| Python | 36.2% |
| Agile | 34.5% |
PM
37 NZ postings in this family
| Term | % of family postings |
|---|---|
| Communication | 48.6% |
| Leadership | 45.9% |
| Stakeholder management | 37.8% |
| Teamwork | 37.8% |
| Security | 21.6% |
| Problem solving | 18.9% |
| SQL | 18.9% |
| Agile | 16.2% |
Full-stack
16 NZ postings in this family
| Term | % of family postings |
|---|---|
| React | 81.3% |
| Mentoring | 75.0% |
| TypeScript | 62.5% |
| AWS | 56.3% |
| CI/CD | 56.3% |
| Leadership | 50.0% |
| Code review | 43.8% |
| Communication | 43.8% |
Method and limitations
How terms were matched
Case-insensitive fixed-vocabulary matching over whitespace-normalized posting text; each term matches any of its alias patterns with word boundaries on both sides of a match (boundaries apply to word characters only, so C#, C++, .NET and Node.js are not broken). Ambiguous common-word terms are matched only via unambiguous aliases, which undercounts them.
How duplicates were removed
Postings are deduplicated by identical normalized full-text hash OR identical first 120 characters of normalized text; the first occurrence is kept.
What we suppress
A term is reported only when it appears in at least 5 deduplicated NZ postings; families with fewer than 15 NZ postings are merged into 'other' without a per-family breakdown; family cells with fewer than 3 mentions are left blank rather than reported as 0.
Limitations
- The postings were collected by a single job seeker applying to software, AI and product roles, so the sample is skewed toward those directions and is not a random sample of the New Zealand market.
- Each posting is the text saved at application time; the same role reposted with different wording across job boards may not be fully removed by text deduplication.
- Keyword hits come from fixed alias patterns: ambiguous terms (for example go, rag, rest, spark) are only matched via unambiguous aliases, which undercounts them.
- A posting counts as mentioning a term if the term appears anywhere in the description; passing mentions and hard requirements are not distinguished.
Download the data
The full keyword table behind this page — every term, category, posting count, percentage and per-family breakdown — as a single CSV. Free to use with a link back to this page (CC BY 4.0).
Download nz-tech-job-keywords-2026.csvCite this dataset
JDMatcher, Skills in 200+ NZ tech job postings — the data, https://resumejdmatcher.com/blog/nz-tech-job-keywords, data collected August–October 2026.
What to do with this
Treat these tables as a sanity check, not a template. Find the family closest to the roles you're applying to, compare its top terms against your resume's skills section, and read the practices list with the same seriousness as the stack. Then verify against the actual posting: pull the keywords from the job description itself and cross-check them with the per-role ATS keyword reference.
When you're ready to act on it, run a free resume check or match your resume against the posting to see exactly which of these terms you're missing.
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