New York Data & Analytics: Python, SQL, AWS Lead 1,052 Roles -- January 2026

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Analysis of 1,087 data and analytics roles across 548 employers in New York City for January 2026. Fintech leads industry hiring at 15% of roles, while enterprise companies account for 52% of openings despite January layoffs reaching their highest levels since 2009.

This report analyzes 1,052 Data & Analytics job postings from 523+ 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

1.0Target fintech and financial services These sectors account for 25% of roles. Capital One alone has 7% of tracked postings, suggesting active hiring programs.

1.1Build Python + SQL + cloud foundation Python (43%) and SQL (34%) remain essential. Add AWS (16%) or Snowflake (13%) to differentiate.

1.2Consider ML specialization Among tracked roles with disclosed salaries, ML Engineers report a $225K median vs $168K for Data Engineers. LLM experience appears in 10% of postings.

1.3Leverage employer-disclosed salary data 19% of tracked roles disclose salary ranges directly. Where available, use this data to benchmark offers and negotiate effectively.

1.4Entry-level candidates face steep competition With a 15:1 senior-to-junior ratio, focus on mid-sized companies and consider consulting roles as entry points.

Skills Demand

54% of roles with skills data

Low

High

Skills insight: Python (43%) and SQL (34%) remain foundational, appearing together in 27% of roles. AWS leads cloud platforms at 16%, with Snowflake (13%) the top data warehouse. AI/ML skills are emerging: general AI (12%), LLMs (10%), and PyTorch (7%) appear frequently. The dbt + SQL pairing (10%) reflects modern analytics engineering practices gaining traction.

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

Director+

+4pp

Biggest Decline

Mid-Level

-2pp

Senior-to-Junior Ratio

15:1

Senior+ roles per Junior role

Entry Accessibility Rate

17%

Junior + Mid-Level roles combined

Senior roles lead at 52%, with Staff/Principal (16%) and Director+ (15%) indicating strong demand for experienced practitioners. Director+ roles gained 3pp, suggesting leadership hiring. Mid-Level (11%) and Junior (6%) combined offer 17% entry accessibility, though the 15:1 senior-to-junior ratio points to a competitive market for those starting their careers.

Working Arrangement

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

97% of roles with known working arrangement

48%Remote

Remote48%

Hybrid25%

Flexible17%

Onsite10%

Remote roles lead at 49%, with hybrid (24%) and flexible (17%) arrangements contributing to 90% total flexibility. Only 10% of roles require full onsite presence. Despite broader return-to-office narratives, data roles in New York maintain high location flexibility, likely reflecting talent competition and the nature of data work.

Role Specialization

Low

High

vs December 2025

Biggest Gainer

ML Engineer

+3pp

Biggest Decline

Product Analytics

-2pp

ML Engineer roles lead at 30% of postings, up 3pp from December and reflecting sustained AI/ML investment. Data Scientist (19%) and Data Engineer (18%) follow, with Data Analyst at 14%. Product Analytics declined 2pp, potentially as companies consolidate analytics functions. Research Scientist roles (3%) indicate ongoing fundamental ML research in the market.

IC vs Management Track

84%IC

Individual Contributor84%

Management16%

Individual contributors account for 84% of roles, with management at 16%. This ratio suggests most data teams are expanding technical capacity rather than adding management layers. The IC-heavy distribution is typical for data functions where hands-on technical work remains central.

Compensation

19% of roles with disclosed salary ranges

Overall Distribution

25th Percentile

$152K

Median

$188K

75th Percentile

$227K

IQR (Spread)

$75K

Advertised Salary by Seniority

Advertised Salary by Role

Market Context

1.January layoffs highest since 2009 Challenger, Gray & Christmas reported January 2026 layoffs at their highest level since 2009. Tech sector continues workforce reductions while maintaining selective technical hiring.

2.Hiring announcements at historic lows January hiring announcements fell to their lowest level since 2009 according to Challenger data. Companies appear to be backfilling critical roles rather than expanding headcount broadly.

3.Employer-disclosed salary data provides compensation benchmarks 19% of tracked roles include salary ranges disclosed directly by employers in their ATS postings. This subset likely reflects higher-confidence compensation data, as predicted or aggregator salary estimates have been excluded.

4.AI investment sustains ML hiring Despite broader hiring slowdowns, ML Engineer roles increased 3pp to lead at 30% of postings. Enterprise AI initiatives appear to be driving continued demand for machine learning talent.

5.Fintech resilience Fintech gained 4pp to lead industry hiring at 15%. New York's position as a financial center continues to drive demand for data talent in financial technology.

Methodology

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

Data collection:

1.Over 1,000 roles from 548+ employers aggregated from multiple sources
2.Recruitment agency postings identified and excluded (6% 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 572 roles with skill data (54% coverage)
3.Salary data available due to pay transparency law
4.Working arrangement based on 257 ATS-sourced roles (Adzuna excluded due to truncated descriptions)

Data coverage:

78%

Seniority coverage

Roles with seniority level classified

97%

Arrangement coverage

Roles with working arrangement known

54%

Skills coverage

Roles with skills extracted from description

59%

Employer metadata

Roles with enriched company data

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