Singapore Data & Analytics: Python, SQL, AWS Lead 230 Roles -- January 2026

Beta

Singapore's data job market in January 2026 shows 252 roles across 127 employers, with strong demand for ML Engineers and growing opportunities in Professional Services and Fintech sectors.

This report analyzes 230 Data & Analytics job postings from 110+ companies tracked via direct employer career pages and job board aggregators. Our coverage skews toward tech-forward and scaling companies; large enterprises using enterprise hiring platforms may be underrepresented. Coverage varies by section and is noted throughout.

Key Takeaways for Job Seekers

1.0Build ML pipeline experience With ML Engineers leading demand at 25%, focus on practical experience with production ML systems, not just model building.

1.1Target Professional Services and Fintech These two sectors account for 34% of roles combined and may offer diverse project exposure across multiple client industries.

1.2Consider Enterprise employers Large companies account for the largest share of hiring at 63% of roles, often providing structured career paths and comprehensive benefits packages.

1.3Working arrangement data unavailable Working arrangement data is not displayed for this market due to insufficient ATS-sourced sample size (44 roles). Candidates should research employer flexibility policies directly.

1.4Pair Python with LLM skills LLMs and RAG appear prominently in skill requirements, suggesting AI application experience could differentiate candidates.

Skills Demand

41% of roles with skills data

Low

High

Skills insight: Python (38%) and SQL (28%) remain foundational requirements, appearing together in 20% of roles. Cloud skills focus on AWS at 13%, while emerging AI capabilities including LLMs (11%) and RAG (7%) reflect growing demand for AI engineers who can build production ML pipelines. The modern data stack (dbt, Airflow, Spark, Databricks) features prominently across infrastructure roles.

Seniority Distribution

Junior: 0-2 years | Mid-Level: 3-5 years | Senior: 6-10 years | Staff/Principal: 11+ years (IC track) | Director+: Management track

Low

High

vs December 2025

Biggest Gainer

Junior

+5pp

Biggest Decline

Senior

-8pp

Senior-to-Junior Ratio

3:1

Senior+ roles per Junior role

Entry Accessibility Rate

31%

Junior + Mid-Level roles combined

Senior roles comprise 42% of openings, with a 3:1 senior-to-junior ratio that suggests moderate entry-level accessibility. Junior roles gained 7 percentage points this month while Senior declined by 9 percentage points, potentially indicating employers are building out their talent pipelines. The 30% entry accessibility rate includes both Junior and Mid-Level positions.

Working Arrangement

Onsite: office full-time | Hybrid: mix of office and remote | Remote: work from anywhere | Flexible: employee chooses arrangement

82% of roles with known working arrangement

39%Remote

Onsite52%

Remote39%

Flexible6%

Hybrid3%

Working arrangement data is not displayed for this market due to insufficient ATS-sourced sample size (44 roles). A minimum of 100 ATS-sourced roles is needed for reliable working arrangement analysis.

Role Specialization

Low

High

vs December 2025

Biggest Gainer

Data Scientist

+4pp

Biggest Decline

Product Analytics

-3pp

ML Engineers lead demand at 25%, reflecting Singapore's focus on AI applications in finance, logistics, and health-tech. Data Scientists, Data Analysts, and Data Engineers each comprise 18-19% of roles, showing balanced demand across the data function. Data Scientist roles gained 3 percentage points month-over-month while Product Analytics declined by 3 percentage points.

IC vs Management Track

89%IC

Individual Contributor89%

Management11%

Individual contributor roles account for 89%, with management positions at 11%. This IC-focused distribution is typical for technical data functions where deep expertise often matters more than team leadership.

Compensation

Compensation data excluded due to low disclosure rates in markets without pay transparency legislation.

Market Context

1.APAC tech hub growth Singapore continues to attract regional headquarters and tech investment, with strong opportunities in ICT, Financial Services, and Professional Services driving data hiring.

2.AI engineering in demand AI engineers with ML pipeline experience top employer shortlists, reflecting enterprise focus on deploying production AI systems rather than experimental research.

3.Sector diversification Finance, logistics, and health-tech sectors are driving data job growth, while Crypto and Web3 hiring has contracted significantly this month.

4.Hardware sector resurgence Semiconductor and electronics hiring gained momentum with Micron among top employers, potentially reflecting regional supply chain investment.

5.Regional talent competition Working arrangement data is not displayed for this market due to insufficient ATS-sourced sample size (44 roles). A minimum of 100 ATS-sourced roles is needed for reliable working arrangement analysis.

Methodology

This report analyzes direct employer job postings for Data & Analytics roles in Singapore during January 2026.

Data collection:

1.Over 200 roles from 127+ employers aggregated from multiple sources
2.Recruitment agency postings identified and excluded (0% of raw data)
3.Jobs deduplicated across sources to avoid double-counting

Classification:

1.Roles classified using an LLM-powered taxonomy
2.Subfamily, seniority, skills, and working arrangement extracted
3.Employer metadata enriched from company databases where available

Limitations:

1.Not a complete census of the market - some roles may not be captured
2.Skills analysis based on 95 roles with skill data (41% coverage)
3.Salary data not included due to low disclosure rates
4.Working arrangement based on 44 ATS-sourced roles (Adzuna excluded due to truncated descriptions)

Data coverage:

73%

Seniority coverage

Roles with seniority level classified

82%

Arrangement coverage

Roles with working arrangement known

41%

Skills coverage

Roles with skills extracted from description

66%

Employer metadata

Roles with enriched company data

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