---
license: cc-by-4.0
pretty_name: Datamata Skill Demand Index
language:
  - en
tags:
  - job-market
  - tech-skills
  - hiring-trends
  - labor-market
  - skills
  - jobs
  - careers
size_categories:
  - n<1K
source_datasets:
  - original
configs:
  - config_name: default
    data_files: skill-demand-index.csv
---

![Datamata Skill Demand Index](dataset-cover-image.png)

# Datamata Skill Demand Index

Daily share of active tech job listings mentioning each skill, across data, engineering, product, DevOps, security and AI. One row per category and skill from the most recent snapshot, including how often each skill is a hard requirement.

- **Latest snapshot:** 2026-07-12
- **Rows in this release:** 669
- **Updated:** daily
- **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — free to use and adapt, including commercially, with attribution.
- **Source & methodology:** <https://www.datamatastudios.com/datasets>

## Quickstart

```python
import pandas as pd

# Stream straight from the Hub — no download step needed
df = pd.read_csv("hf://datasets/datamatastudios/skill-demand-index/skill-demand-index.csv")

# Highest-demand skills right now
print(df.sort_values("demand_pct", ascending=False).head(10))
```

Or load it with the 🤗 `datasets` library:

```python
from datasets import load_dataset

ds = load_dataset("datamatastudios/skill-demand-index")
```

## What you can answer with it

- Which skills lead demand in data, engineering, product, DevOps, security or AI — and by how much.
- How often a skill is a **hard requirement** versus nice-to-have (`required_count` vs `listing_count`).
- How a skill's demand share moves over time, by appending each daily snapshot.

## Columns

| Column | Type | Description |
|---|---|---|
| `snapshot_date` | string | UTC date the snapshot was computed (YYYY-MM-DD). |
| `category` | string | Role category: data, engineering, product, devops, security or ai. |
| `skill` | string | Normalised skill name. |
| `skill_group` | string | Skill family the skill belongs to (e.g. language, cloud, framework). |
| `listing_count` | number | Active listings in the category that mention the skill. |
| `total_listings` | number | Total active listings in the category on that date. |
| `demand_pct` | number | listing_count / total_listings x 100, rounded to 0.1. |
| `required_count` | number | Listings where the skill is a hard requirement (vs nice-to-have). Blank for rows snapshotted before this was tracked. |

## How it is built

Active tech job listings are scraped daily from public applicant-tracking systems
(Greenhouse, Lever, Ashby) and aggregated boards. For each role category the demand
share of a skill is `listings_with_skill / total_active_listings x 100`. This
release is the most recent daily snapshot for all six categories. Full method and
known limitations: <https://www.datamatastudios.com/methodology>.

## Citation

> Datamata Studios. "Datamata Skill Demand Index." 2026-07-12. https://www.datamatastudios.com/datasets. Licensed under CC BY 4.0.