Notably, Architecture and Engineering Occupations jobs accounted for a 14% share of the global mining industry’s batteries-related total new job postings in Q2 2023, down 47% over the prior quarter.
Architecture and Engineering Occupations drive batteries-related hiring activity
Architecture and Engineering Occupations, with a share of 14%, emerged as the top batteries-related job roles within the mining industry in Q2 2023, with new job postings drop by 47% quarter-on-quarter. Office and Administrative Support Occupations came in second with a share of 13% in Q2 2023, with new job postings rising by 15% over the previous quarter.
The other prominent batteries roles include Management Occupations with an 8% share in Q2 2023, Computer and Mathematical Occupations with a 6% share of new job postings.
Top five companies in mining industry accounted for 46% of hiring activity
The top companies, in terms of number of new job postings tracked by GlobalData, as of Q2 2023 were Schnitzer Steel Industries, Caterpillar, Wartsila, Cummins, and Rio Tinto. Together they accounted for a combined share of 46% of all batteries-related new jobs in the mining industry.
Schnitzer Steel Industries posted 150 batteries-related new jobs in Q2 2023, Caterpillar 136 jobs, Wartsila 60 jobs, Cummins 60 jobs, and Rio Tinto 54 jobs, according to GlobalData’s Job Analytics.
Hiring activity was driven by the US with a 52.75% share of total new job postings, Q2 2023
The largest share of batteries-related new job postings in the mining industry in Q2 2023 was in the US with 52.75% followed by Australia (21.12%) and Canada (6.51%). The share represented by the US was two percentage points higher than the 50.81% share it accounted for in Q1 2023.
For further understanding of GlobalData’s Batteries – Thematic Research buy the report here.
This content was updated on 24 July 2023
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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData’s Jobs Analytics uses machine learning to uncover key insights from tracking daily job postings for thousands of companies globally. Proprietary analysis is used to group jobs into key thematic areas and granular sectors across the world’s largest industries. classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.