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 Hiring Managers

1.0ML talent commands premium Among roles with disclosed salaries, ML Engineers show a $225K median vs $168K for Data Engineers. Budget accordingly for AI/ML initiatives.

1.1Remote policies remain competitive advantage 49% of roles offer full remote. Restricting to onsite-only (10% of market) may limit candidate pools.

1.2Junior pipeline underdeveloped Only 6% junior roles creates long-term talent gaps. Consider structured programs to build internal talent.

1.3Salary benchmarks available for disclosed roles 19% of tracked roles include employer-disclosed salary ranges. Where competitors disclose, candidates may arrive with clear benchmarks. Ensure ranges are competitive or explain total comp.

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

Employers Hiring for Data & Analytics Roles

Low

High

vs December 2025

Biggest Gainer

Capital One

+3pp

New This Month

NBCUniversal, PwC, SoFi

Market interpretation: Capital One leads tracked hiring with 7% of roles, up 3pp from December. JPMorgan Chase appears under multiple name variations, indicating employer name normalization opportunities. New entrants include PwC, NBC Universal, and Instacart, reflecting cross-industry data team expansion. The top 15 employers account for 21% of postings.

Industry Distribution

52% of roles with industry data

Low

High

vs December 2025

Biggest Gainer

Fintech

+4pp

Biggest Decline

Data Infrastructure

-3pp

Fintech leads at 15%, gaining 4 percentage points from December, likely reflecting ongoing digital finance investment. Combined with Financial Services (10%), finance-related sectors account for a quarter of the market. Data Infrastructure declined 3pp, possibly indicating consolidation in the data tooling space. Coverage of 52% suggests industry classifications are available for the majority of roles.

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.

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.

Company Maturity

49% of roles with company age data

42%Growth Stage

Mature (>15 yrs)49%

Growth (6-15 yrs)42%

Young (<=5 yrs)9%

Mature companies (15+ years) lead with 48% of roles, followed closely by Growth-stage firms (42%). This balance suggests both established enterprises and scaling companies are actively hiring. Young companies (5 years or less) account for just 9%, indicating that early-stage startups may be more cautious about data team expansion in the current economic climate.

Ownership Type

50% of roles with ownership data

54%Private

Private54%

Public36%

Subsidiary9%

Acquired1%

Private companies lead at 55%, with public companies contributing 35% of roles. This mix reflects New York's diverse corporate landscape spanning venture-backed startups, private equity-owned firms, and major public corporations. Subsidiaries account for 9%, often representing the local offices of global enterprises.

Employer Size Distribution

49% of roles with company size data

53%Enterprise

Enterprise (1,000+)52%

Scale-up (50-1,000)27%

Startup (<50)21%

Enterprise companies (1,000+ employees) account for 52% of roles, reflecting New York's concentration of large financial institutions, media companies, and tech giants. Scale-ups (27%) and startups (21%) contribute nearly half of openings, suggesting opportunities across company sizes despite enterprise concentration.

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.

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.

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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