Tech Demand

What is worth learning · reported week 2026-W44 (last completed ISO week, SGT) · 6+ yrs · Data
Experience: all0-23-56+unstated
Role: allAI-MLBackendDataFrontendFullstackMobileOther-ITPlatformSRESecurity

1. Demand ranking

24 enriched SWE postings in 2026-W44. 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.

sql23python20spark11aws9dbt9kafka9git8airflow7terraform7azure6mssql3shell3snowflake3ansible2bigquery2

2. Momentum (vs the previous 4 weeks)

Heating up

TechnologyShareChangePostings
sql95.8%+26.5pp23
python83.3%+15.5pp20
spark45.8%+7.7pp11

Cooling down

Nothing fell this week.

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$11000, the median of 372 postings advertising a monthly range — medians pin the unit so the figures are comparable. Separately, 100.0% of SWE postings state pay at all (372 of 372, 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
sqllanguage2395.8% +0.0% 0.0%
pythonlanguage2083.3% +0.0% 0.0%
sparkframework1145.8% +0.0% 0.0%
awscloud937.5% -4.5% 0.0%
dbttool937.5% -13.6% 0.0%
kafkatool937.5% -2.3% 0.0%
gittool833.3% -4.5% 0.0%
airflowtool729.2% -2.3% 0.0%
terraformtool729.2% -4.5% 0.0%
azurecloud625.0% -2.3% 0.0%
mssqldatabase312.5% -9.1% 0.0%
shelllanguage312.5% -4.5% 0.0%
snowflakedatabase312.5% +0.0% 0.0%
ansibletool28.3% —(n=7) 0.0%
bigquerydatabase28.3% -13.6% 0.0%
golanguage28.3% —(n=9) 0.0%
grpctool28.3% —(n=6) 0.0%
javalanguage28.3% +4.5% 0.0%
machine-learningai28.3% +9.1% 0.0%
mysqldatabase28.3% -2.3% 0.0%
redisdatabase28.3% —(n=15) 0.0%
scalalanguage28.3% +4.5% 0.0%
springframework28.3% —(n=7) 0.0%
dockertool14.2% +0.0% 0.0%
generative-aiai14.2% +4.5% 0.0%
google-cloudcloud14.2% -9.1% 0.0%
grafanatool14.2% —(n=3) 0.0%
kubernetestool14.2% +0.0% 0.0%
linuxtool14.2% -4.5% 0.0%
nodejslanguage14.2% —(n=11) 0.0%

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 (2026-08-08 → 2026-11-05) across 372 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
Python8923.9%15.7%
Data Pipeline8322.3%3.6%
Computer Science7720.7%0.0%
Data Engineering7720.7%23.4%
Data Governance6818.3%7.4%
SQL6818.3%16.2%
Databricks6718.0%9.0%
AWS5214.0%9.6%
ETL Tools5214.0%5.8%
PySpark4913.2%22.4%
Apache Spark4812.9%10.4%
Data Science4612.4%15.2%
Design4612.4%0.0%
Data Lake4111.0%7.3%
ETL3810.2%15.8%
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.