Agency Partners
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.
In Germany, the job market for Data Data Science Engineer roles has exhibited notable fluctuations over the past 12 weeks. The count of new job postings surged significantly in week 21, with 205 positions opened, suggesting a peak in demand. However, this spike contrasts sharply with the weekly closures, which peaked at 94 jobs closed in week 24. Overall, the weekly data indicates that while the demand for Data Data Science Engineers remains robust, recruitment strategies must adapt to manage a substantial number of positions being closed, highlighting the competitive nature of the hiring landscape compared to other tech roles across Europe.
| Company name | Country | Industry | Founded | # Job openings | |
|---|---|---|---|---|---|
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TieTalent | Switzerland | Information Technology & Services | 2017 | 14 |
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adesso SE | Germany | Information Technology & Services | 1997 | 14 |
|
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KPMG Deutschland | null | null | null | 12 |
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Canonical | United Kingdom | Information Technology & Services | 2004 | 10 |
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ALDI SÜD | Germany | Retail | 1913 | 10 |
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Instaffo | Germany | Information Technology & Services | 2014 | 5 |
|
Ubique Systems | United Kingdom | Information Technology & Services | 2000 | 4 |
|
SR2 | Socially Responsible Recruitment | Certified B Corporation™ | United Kingdom | Information Technology & Services | 2017 | 4 |
|
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Circunomics | Germany | Renewables & Environment | 2019 | 4 |
|
|
Delivery Hero | Germany | Information Technology & Services | 2011 | 4 |
In the current landscape of the Data Data Science Engineers job market, Germany stands out with a substantial number of job openings compared to its available talent pool. With a count of X job openings and a talent pool size of Y, the jobs-to-talent ratio indicates a challenging hiring environment, notably more competitive than in neighboring countries like France, which shows a ratio of A, and the Netherlands with a ratio of B. This disparity signals that hiring managers may need to implement more innovative recruitment strategies for CTOs in Germany's tech sector to attract the necessary talent. Additionally, the increasing demand for Data Data Science Developers in Germany may necessitate a focus on talent retention and development alongside recruitment efforts. As hiring trends evolve, understanding these dynamics is crucial for effective workforce planning within the technology sector across Europe.
In the German job market for Data Data Science Engineering, the distribution of seniority levels reveals an increasing trend towards experienced candidates. Entry-level positions account for 42% of the job openings, while Mid-Senior level roles follow closely with 38%. Associate level positions make up 12% of the total opportunities, indicating a notable emphasis on attracting talent at these foundational and intermediary stages.
In the German job market for engineering roles, full-time positions dominate, comprising 96% of available roles, followed by part-time opportunities at 4%. Internships and contract roles represent a smaller fraction, accounting for 2% and less than 2% respectively. This distribution highlights the need for hiring managers to focus on securing full-time talent to meet the increasing demand for Data Data Science Engineers in Germany.
The time to hire for Data Science Engineer positions in Germany reveals critical insights for hiring managers focused on improving their recruitment strategies. Notably, the most significant portion of candidates, totaling 278, were hired within 30 days, indicating a trend towards a quicker recruitment process in the competitive Data Data Science job market in Germany. This is followed by a notable count of 225 hires made within 10 days, which underscores the urgency for hiring managers and CTOs to streamline their hiring processes. The data suggests that while many positions are filled promptly, there remains a substantial portion of candidates taking 25 days or more to recruit. As hiring trends evolve, understanding these dynamics in the Data Data Science Engineer hiring landscape can greatly aid in strategic decision-making and positioning within the technology sector.
The Data Data Science job market in Estonia has experienced notable fluctuations over the past three months, with a peak of 9 new job openings in week 20, but only 1 new opening in week 23 and weeks 26 and 27, highlighting challenges in retaining talent in this competitive sector.
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The Data Engineers job market in Sweden, particularly in Solna, has shown fluctuating trends, with 10 new job openings reported in week 19, followed by significant declines, indicating a net decline in available positions.
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The job market for Data Engineers in Portugal is currently experiencing a robust demand, with a notable increase in openings, peaking at 31 new roles posted in week 27, indicating significant opportunities for Data Data Engineer candidates.
View ReportIn Germany, the distribution of Data Engineers job openings reveals a concentration in major urban centers. Berlin leads with 42% of the total job openings, followed by Munich at 19% and Hamburg at 14%. This data underscores the capital's role as a critical hub in the Data Data Science job market in Germany, further discussed in the accompanying chart.
In the competitive landscape of the Data Data Science job market in Germany, several technologies stand out as essential for professionals looking to excel. Python leads with an impressive frequency of 7,433, reflecting its dominance in data analysis and machine learning applications. SQL follows closely, with 2,500 occurrences, highlighting its importance for data manipulation and querying. Java, a critical language for enterprise applications, shows a significant usage of 2,483. Machine learning frameworks, anchored by the widespread application of AI with a frequency of 1,974, further emphasize the growing reliance on intelligent systems in data science projects. The accompanying chart illustrates these trends, providing hiring managers with key insights into the technologies that candidates are likely to be proficient in.
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