Tech Demand

What is worth learning · reported week 2026-W37 (last completed ISO week, SGT) · 0-2 yrs · Data
Experience: all0-23-56+unstated
Role: allAI-MLBackendDataFrontendFullstackMobileOther-ITPlatformSRESecurity

1. Demand ranking

27 enriched SWE postings in 2026-W37. Share = postings mentioning the technology ÷ that number — postings still awaiting enrichment are excluded from the denominator, so a processing backlog cannot depress every share at once. The chart shows the top 15; the table in section 3 lists the top 30.

python15sql14machine-learning9aws6azure4llm3mssql3postgresql3spark3deep-learning2google-cloud2hadoop2openai2rag2angular1

2. Momentum (vs the previous 4 weeks)

Heating up

Nothing rose this week.

Cooling down

TechnologyShareChangePostings
sql51.9%-18.2pp14
python55.6%-14.9pp15

Change is in percentage points of share, not relative percent: a technology going from 1 to 3 postings would otherwise read as +200% and top the board. Boards consider every technology above the bar, not only the 30 the table below shows.

3. Salary premium and entry-friendliness

Premium compares the median advertised monthly salary of postings mentioning a technology against the overall median, over the trailing 90 days. Baseline: S$5500, the median of 269 postings advertising a monthly range — medians pin the unit so the figures are comparable. Separately, 100.0% of SWE postings state pay at all (269 of 269, in any unit); the rest hide it, and no figure here describes them. Entry-friendly is computed over the same 90-day window. Premium mixes seniority in (senior roles name more infrastructure); pick an experience band above to compare within one. Entry-friendly = the share of postings mentioning the technology that ask for at most 2 years' experience, or are Intern/Junior roles with no stated requirement. The table lists the top 30 technologies by postings.

TechnologyKindPostingsShareSalary premiumEntry-friendly
pythonlanguage1555.6% +9.1% 100.0%
sqllanguage1451.9% +9.1% 100.0%
machine-learningai933.3% +13.6% 100.0%
awscloud622.2% +0.0% 100.0%
azurecloud414.8% -4.5% 100.0%
llmai311.1% +9.1% 100.0%
mssqldatabase311.1% +0.0% 100.0%
postgresqldatabase311.1% +9.1% 100.0%
sparkframework311.1% +13.6% 100.0%
deep-learningai27.4% +22.7% 100.0%
google-cloudcloud27.4% +9.1% 100.0%
hadooptool27.4% +9.1% 100.0%
openaiai27.4% —(n=6) 100.0%
ragai27.4% —(n=15) 100.0%
angularframework13.7% —(n=7) 100.0%
cpplanguage13.7% —(n=11) 100.0%
dockertool13.7% —(n=19) 100.0%
generative-aiai13.7% +14.5% 100.0%
gittool13.7% +16.4% 100.0%
kubernetestool13.7% —(n=19) 100.0%
nlpai13.7% —(n=12) 100.0%
pytorchai13.7% +9.1% 100.0%
scalalanguage13.7% +77.3% 100.0%
shelllanguage13.7% —(n=9) 100.0%
tensorflowai13.7% +9.1% 100.0%

4. What else they ask for

These are MyCareersFuture's own skill tags — the competencies the employer filled in on the form, over the trailing 90 days (2026-06-23 → 2026-09-20) across 269 postings. They are not the technology ranking above: languages and frameworks appear only in the free-text description, which is why this system reads it separately. "Must-have" is the share of postings listing the tag that marked it essential rather than desirable — a tag that is everywhere but rarely essential is table stakes, one that is usually essential is a filter someone is applying.

SkillPostingsShareMarked must-have
Python9133.8%9.9%
SQL7829.0%11.5%
Computer Science7026.0%0.0%
Statistics6323.4%1.6%
Machine Learning6223.0%1.6%
Data Science5420.1%1.9%
Data Analysis5319.7%13.2%
Data Engineering4516.7%8.9%
Power BI4115.2%4.9%
Data Pipeline3713.8%8.1%
Liaising with cross functional teams3613.4%5.6%
Artificial Intelligence3513.0%11.4%
Tableau3111.5%6.5%
Data Modelling3011.2%0.0%
Mathematics2910.8%0.0%
Numbers computed by SQL from public MyCareersFuture data; data is refreshed daily, so it lags the live market by up to 24h. Methodology: docs/03-data-model.md · data freshness · Compliance: aggregate statistics only, no personal data.