language:
- en
license: unknown
task_categories:
- text-classification
- text-retrieval
- feature-extraction
pretty_name: Djinni Job Vacancies
size_categories:
- 1K<n<10K
tags:
- jobs
- recruitment
- hiring
- careers
- ukraine
- software-engineering
- nlp
Djinni Job Vacancies Dataset
Dataset Summary
This dataset contains 8,270 job vacancies collected from the Djinni job platform. It includes structured metadata together with full job descriptions, making it useful for Natural Language Processing (NLP), Information Retrieval (IR), recommendation systems, labor market analysis, and machine learning research.
Each record corresponds to a single job posting.
Supported Tasks
The dataset can be used for:
- Job recommendation systems
- Semantic search and retrieval
- Information extraction
- Skill extraction
- Salary prediction (after enrichment)
- Job classification
- Occupation taxonomy mapping
- Language modeling
- Labor market analytics
- Embedding generation for Retrieval-Augmented Generation (RAG)
Languages
Primary language: English
Some metadata may contain multilingual content depending on the original job posting.
Dataset Structure
Data Instances
Example:
{
"URL": "https://djinni.co/jobs/829413...",
"Title": "Senior DevOps Engineer",
"Company": "Example Company",
"Description": "We are looking for...",
"Category": "DevOps",
"Skills_Tags": "AWS, Kubernetes, Terraform",
"Languages": "English",
"Experience_Text": "3+ years",
"Experience_Months": 36,
"Employment_Type": "Full-time",
"Work_Format": "Remote",
"Location": "Ukraine",
"Domain": "Cloud",
"Company_Type": "Product",
"Views": 215,
"Applications": 12,
"Published_Date": "3 June"
}
Data Fields
| Column | Description |
|---|---|
| URL | Original job posting URL |
| Title | Job title |
| Company | Company name |
| Description | Full textual job description |
| Category | Job category or specialization |
| Skills_Tags | Technologies and skills listed in the vacancy |
| Languages | Required languages |
| Experience_Text | Human-readable experience requirement |
| Experience_Months | Parsed minimum experience in months |
| Employment_Type | Employment type (e.g., Full-time, Contract) |
| Work_Format | Remote, Hybrid, Office, etc. |
| Location | Job location |
| Domain | Industry or business domain |
| Company_Type | Company type (e.g., Product, Outsourcing, Startup) |
| Views | Number of page views |
| Applications | Number of applications |
| Published_Date | Publication date as displayed on Djinni |
Dataset Size
- Number of rows: 8,270
- Number of columns: 17
Source Data
Data Collection
The dataset was collected from publicly accessible job postings on the Djinni recruitment platform.
Metadata and textual job descriptions were extracted and normalized into a structured CSV format.
Source
Djinni
Uses
Direct Use
- Semantic job search
- Resume-job matching
- Skill extraction
- Named Entity Recognition
- Embedding generation
- Job recommendation
- Labor market analysis
Out-of-Scope Use
This dataset should not be used to:
- Infer personal characteristics of individuals
- Make automated hiring decisions
- Evaluate applicants
Biases
The dataset reflects vacancies available on Djinni during the collection period and therefore:
- overrepresents companies using the platform,
- primarily reflects the software engineering labor market,
- may underrepresent certain regions or occupations.
Limitations
- No salary information.
- Publication dates are stored as displayed on the website.
- Company information depends on what employers provide.
- Some textual fields may contain HTML remnants or formatting artifacts.
Citation
If you use this dataset in academic work, please cite:
@dataset{djinni_jobs,
title={Djinni Job Vacancies Dataset},
author={Your Name},
year={2026},
publisher={Hugging Face}
}
License
The licensing status of the original job postings should be reviewed before commercial redistribution. This repository currently specifies unknown until an appropriate license can be confirmed.
Acknowledgements
Thanks to Djinni for providing a platform with publicly accessible job listings that enable research into labor market trends, information retrieval, and natural language processing.