Analysis of Core Technology Stacks for Big Data Engineers Based on Recruitment Data Mining

Minjia Zhou

doi:10.47297/wspeiWSP2516-253513.20250906

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Analysis of Core Technology Stacks for Big Data Engineers Based on Recruitment Data Mining

9卷第6期

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Analysis of Core Technology Stacks for Big Data Engineers Based on Recruitment Data Mining
Analysis of Core Technology Stacks for Big Data Engineers Based on Recruitment Data Mining
Faculty of Science, Civil Aviation Flight University of China, Chengdu, Sichuan, 641419, China
2025年9卷第6期页码：67-71
纸质出版：2025-12-30
DOI：10.47297/wspeiWSP2516-253513.20250906
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Minjia Zhou. (2025). Analysis of Core Technology Stacks for Big Data Engineers Based on Recruitment Data Mining. 创业与创新（英文版）, 9(6), 67-71.

Zhou Minjia.Analysis of Core Technology Stacks for Big Data Engineers Based on Recruitment Data Mining[J].Entrepreneurship and Innovation,2025,09(06):67-71.
Minjia Zhou. (2025). Analysis of Core Technology Stacks for Big Data Engineers Based on Recruitment Data Mining. 创业与创新（英文版）, 9(6), 67-71. DOI： 10.47297/wspeiWSP2516-253513.20250906.

Zhou Minjia.Analysis of Core Technology Stacks for Big Data Engineers Based on Recruitment Data Mining[J].Entrepreneurship and Innovation,2025,09(06):67-71. DOI： 10.47297/wspeiWSP2516-253513.20250906.

摘要

Abstract

During the job-seeking process

many students face information asymmetry due to a lack of clarity regarding specific technical requirements for various positions. To address this issue

this study examines recruitment data for Big Data Engineers sourced from a Chinese campus recruitment platform. Utilizing Selenium-based automated web scraping

raw data were collected and subsequently processed through data cleaning

text mining

and word frequency analysis to extract core technology stacks. The findings were visually represented using word cloud visualizations.Research results demonstrate that the core technology stacks for Big Data Engineers are concentrated in several key domains—programming languages

data storage

big data frameworks

artificial intelligence technologies

Network Technology and utility tools. This study provides graduates with a data-driven reference for technical requirements based on real-world recruitment trends and offers a reproducible methodology for data mining research involving Chinese-language recruitment information.

关键词

Keywords

references

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Zeng J. , Liao S. Z. , & Chen Y . X . ( 2025 ). Analysis and visualization research of AI job recruitment data based on Python. Modern Information Technology , 9 ( 13 ), 90 – 94 .

Zhang S . Q . ( 2024 ). Python-based data crawling and visualization analysis of big data recruitment posts on a direct recruitment platform. Computer Knowledge and Technology , 20 ( 36 ), 63 – 66 .

Tong F. , & Xu J . N . ( 2024 ). Analysis of professional talent positions and skill requirements based on text mining: A case study of the accounting profession. Commercial Accounting , ( 09 ), 126 – 129 .

Xu Z. L. , Wen B. X. , Xie M. Y. , et al . ( 2021 ). Research on AI job demand analysis based on big data technology . Guangxi Sciences , 28 ( 03 ), 321 – 329 .

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