What Do Data Teams Look Like in 2026?

Data Scientists and Data Engineers make up over half of all roles

Traditional data roles (Tier 1) outnumber AI-specific roles (Tier 2) by 3.6:1. The AI wave added new role types without replacing the existing ones.

Tier 1 = pre-2023 roles. Tier 2 = AI-era roles (AI Engineer, Research Scientist, MLOps, etc.).

Data Engineer and Data Scientist are table stakes. AI Engineer is catching up.

72% of companies have at least one Data Engineer. AI Engineer is already at 37% adoption. Prompt Engineer (2%) is not a real job category yet.

% of the 188 companies with visible roles that have at least one person in each role type.

AI role mix varies 4× by industry

At AI/ML companies, 43% of the data team works in AI-specific roles. At fintech companies, it's 9%. This is about team shape, not team size.

Median Tier 2 share (AI-specific roles as % of data/AI team). Verticals with n<10 excluded.

AI-native teams are 3× more AI-specialized

AI-native companies (AI/ML product, founded after 2018) have a median 47% Tier 2 share vs 16% for traditional. Different team shape, not just different size.

Each dot is one company. Tier 2 share = AI-specific roles as % of data/AI team.

Data leadership formalizes after Series C

Only 10-12% of Series B/C companies have a VP/Head of Data or CDO. It jumps to 33% at Series D and 48% for public companies.

% of companies with identifiable data/AI leadership on LinkedIn (VP Data, Head of AI, CDO, etc.).

Explore the full dataset

Search and sort all 213 companies. Click column headers to sort. T2 Share = AI-specific roles as % of data team.