Agency Partners
This report was last updated on Aug 9, 2025
I analyze live hiring data and tech job trends across Europe to give CTOs and Product Leaders a strategic edge. By tracking tens of thousands of open roles each week, I uncover which skills, roles, and locations are in highest demand — potential competitors, typical time to hire, talent pool sizes, and more to help you prioritize hiring, benchmark and stay competitive in a fast-moving market.
The Data Engineering job market in Denmark has shown fluctuating trends over the past 12 weeks, with a notable peak during week 20 where 59 new positions were opened. However, the closing of jobs has often mirrored these openings, particularly in weeks 21 to 23, indicating a competitive landscape for Data Engineers. On average, there were 25 new Data Developer roles posted weekly, contrasted by a significant number of closures, suggesting that hiring managers need to be proactive in their recruitment strategies to secure top talent. Compared to other roles in Denmark's tech sector, Data Engineering positions are experiencing a dynamic cycle, similar to trends noted in other European countries, reinforcing the necessity for effective hiring and retention strategies.
| Company name | Country | Industry | Founded | # Job openings | |
|---|---|---|---|---|---|
|
Novonesis | Denmark | Research | null | 8 |
|
Netcompany | Denmark | Information Technology & Services | 2000 | 7 |
|
DataAnnotation | United States | Information Technology & Services | null | 7 |
|
the LEGO Group | Denmark | Mechanical Or Industrial Engineering | 1932 | 7 |
|
twoday | United States | Information Technology & Services | 2022 | 6 |
|
Dalux | Denmark | Information Technology & Services | 2005 | 5 |
|
|
Port of Hamburg Marketing | null | null | null | 4 |
|
Eaton | Ireland | Electrical/electronic Manufacturing | 1911 | 4 |
|
Københavns Kommune | Denmark | Government Administration | null | 4 |
|
|
GlobalConnect | Sweden | Telecommunications | 1998 | 4 |
The Data Engineers job market trends in Denmark reveal a competitive environment, particularly when compared to other European nations such as Germany, France, and the Netherlands. With a significant number of job openings juxtaposed against a relatively smaller talent pool, the jobs-to-talent ratio indicates that hiring Data Engineers in Denmark is challenging. For instance, while Denmark may have fewer available candidates per position than Germany, where the recruitment environment is more favorable, it is essential for hiring managers—such as CTOs and Engineering Managers—to develop effective recruitment strategies tailored to this unique landscape. As Data Developer opportunities increase, the future demand for Data Engineers will likely intensify, making proactive hiring approaches crucial for success in Denmark's tech sector.
The seniority distribution of Data Engineering positions in Denmark indicates a strong prevalence of Mid-Senior level roles, comprising 48% of the job market. Entry level positions follow closely, making up 26%, while internships account for 14%. This distribution highlights the emphasis on attracting skilled professionals in the Data Engineering job market, providing insights for hiring managers looking to align their recruitment strategies with current market trends.
In Denmark's engineering job market, the dominant employment type is full-time positions, comprising 93% of available roles. Contract jobs follow, making up 6% of the market, while part-time opportunities account for a modest 1%. This distribution highlights the preference for stability among employers and the increasing need for dedicated Data Engineers in the landscape.
The time to hire distribution for Data jobs in Denmark reveals notable trends that hiring managers in the tech sector should consider. A significant concentration of hires occurs between 25 to 30 days, with 114 and 255 roles filled, respectively. This indicates a prevalent timeframe for recruitment within the Data job market in Denmark. Moreover, about 68 positions take 15 days to hire, while 71 roles are filled within 20 days, suggesting that efficient recruitment strategies can lead to successful placements in a competitive landscape. By understanding these hiring trends, CTOs and engineering managers can adapt their recruitment strategies to align with market expectations, particularly for Senior Data Developers and emerging talent across Europe.
The Data Data Engineer job market in Denmark has seen the opening of 40 new roles in the past 12 weeks, indicating a stable demand amidst low closure rates, with only 21 jobs closed during this period.
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The Data Data Science Engineers job market in Sweden is experiencing significant fluctuations, with 44 new positions posted in week 27 alone, showcasing an increasing demand that outpaces the current talent pool.
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The Data Engineer job market trends in Poland, specifically in Warsaw, present a compelling landscape for hiring managers as they navigate recruitment strategies.
View ReportIn Denmark, the location distribution for Data Engineer job openings reveals significant concentrations in key cities. Copenhagen leads with 78% of the total job postings, demonstrating its status as the primary tech hub. Aarhus follows at 18%, while Ballerup accounts for 4%, indicating a pronounced centralization of opportunities within the capital and the surrounding areas. For further insights, refer to the accompanying chart showcasing these distribution trends.
The data job market in Denmark reveals a clear preference for several core technologies, as illustrated in the accompanying chart. Python stands out with a frequency of 9,057, establishing it as a fundamental programming language for Data Engineers. Following closely are SQL and its dual mentions, which together reflect a combined frequency of 8,396, underscoring its critical role in database management and data querying tasks. Other significant technologies include ETL processes, pivotal for data integration, tracked at 3,343, and Machine Learning, with a notable frequency of 3,188, highlighting the growing importance of predictive analytics. Additionally, the prominence of Azure and AWS points to a strong trend towards cloud-based solutions in the Data Engineering domain, catering to modern data infrastructure needs.
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