# Skills + Pay Index

> An independent index of which skills data, analytics and AI employers ask for in job postings, and what those postings pay. Built from public job-board APIs (Greenhouse, Lever, Ashby), snapshotted daily, reported by week. Aggregates only: no job postings, titles, links or per-company data are republished.

As of October 22, 2026 (week 2026-W43), the index covers 13,293 open data & AI postings at 3,317 companies from 10,956 company job boards, measured against a fixed taxonomy of 151 skills and 12 role families. The most-requested skills right now: Python (67.0%), SQL (40.9%), LLMs (34.9%), AI agents (30.2%), APIs / REST (29.9%). Daily snapshots started on 2026-10-18.

## When to use this site

- You need how often a data, analytics or AI skill (for example Python, SQL, Databricks, Snowflake, dbt, Spark, LLMs, RAG) appears in current job postings, as a share of all data & AI postings.
- You need the median published US pay (USD, annualized) for postings that mention a skill, or for a data & AI role, by level.
- You want to compare demand for data platforms (Databricks vs Snowflake vs BigQuery vs Fabric) or GenAI skills in hiring.
- You want week-over-week movement in skill demand (available once two weeks of daily snapshots exist).
- Do not use it for individual job listings, salaries of specific people or companies, non-data roles, or non-US pay. Pay reflects only ranges employers chose to publish, mostly in US states that require them.

## How to use it

- For exact numbers, read the CSV below rather than scraping HTML.
- Any page is available as Markdown: request it with the header `Accept: text/markdown`.
- Every page states the date its data was taken ("data as of"). Quote that date with any figure.

## Key pages

- [The index (home)](https://datapayindex.com/): top skills, pay by role and level, data platforms, GenAI skills
- [All skills, ranked](https://datapayindex.com/skills/): one page per skill at /skills/<skill>/ with share, companies, pay by level and the roles that ask for it
- [Roles](https://datapayindex.com/roles/): one page per role family
- [AI Engineer](https://datapayindex.com/roles/ai-engineer/)
- [Machine Learning Engineer](https://datapayindex.com/roles/ml-engineer/)
- [Data Engineer](https://datapayindex.com/roles/data-engineer/)
- [Data Scientist](https://datapayindex.com/roles/data-scientist/)
- [Data Analyst](https://datapayindex.com/roles/data-analyst/)
- [Data & AI leadership](https://datapayindex.com/roles/data-leadership/)
- [AI Research Scientist](https://datapayindex.com/roles/research-scientist/)
- [Data Architect](https://datapayindex.com/roles/data-architect/)
- [Analytics Engineer](https://datapayindex.com/roles/analytics-engineer/)
- [Database Engineer / DBA](https://datapayindex.com/roles/database-engineer/)
- [Data Governance & Quality](https://datapayindex.com/roles/data-governance/)
- [BI Developer / Analyst](https://datapayindex.com/roles/bi-analyst/)
- [Methodology](https://datapayindex.com/methodology/): sources, classification, pay rules, limitations
- [Articles](https://datapayindex.com/articles/)
- [The highest-paying data & AI skills in 2026, and why the list misleads](https://datapayindex.com/articles/highest-paying-data-ai-skills/): published 2026-10-21
- [About](https://datapayindex.com/about/)
- [What's new](https://datapayindex.com/changelog/)
- [Contact](https://datapayindex.com/contact/)

## Data

- [Aggregates CSV](https://datapayindex.com/data/aggregates.csv): columns week, as_of, dimension, key, name, level, postings, share_pct, companies, wow_change_pts, median_pay_usd, pay_n. Dimensions include skills, roles, levels and pay by level.
- License: Creative Commons Attribution 4.0 (CC BY 4.0), https://creativecommons.org/licenses/by/4.0/

## Update frequency

Job boards are snapshotted once a day and the site is rebuilt from the latest snapshot. Figures are reported by ISO week. The current data is as of October 22, 2026.

## How to cite

Source: Skills + Pay Index (https://datapayindex.com/), data as of October 22, 2026. Link to the page or the CSV you used.

## Contact

hello@datapayindex.com (https://datapayindex.com/contact/)