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 Hamburg's tech sector, the Data Data Science Engineer job market has shown sporadic growth over the last 12 weeks, with a noticeable spike in week 21, where 9 new positions were posted, showcasing an emerging trend in hiring for these roles. However, the number of closed positions has been relatively consistent, averaging around 2 to 3 closures per week. When compared to other roles within Germany Hamburg, Data Data Science Engineers appear to be experiencing an upward trajectory in job openings, contrasting with a more stable trend in other sectors. Furthermore, this trend aligns with broader patterns observed across Europe, where demand for Data Data Science professionals remains strong, indicative of a robust recruitment landscape.
| Company name | Country | Industry | Founded | # Job openings | |
|---|---|---|---|---|---|
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TieTalent | Switzerland | Information Technology & Services | 2017 | 102 |
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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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ALDI SÜD | Germany | Retail | 1913 | 10 |
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Canonical | United Kingdom | Information Technology & Services | 2004 | 9 |
|
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Jobster | Netherlands | Information Technology & Services | 2023 | 6 |
|
Instaffo | Germany | Information Technology & Services | 2014 | 5 |
|
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HUK-COBURG | Germany | Insurance | 1933 | 5 |
|
|
Nanz medico | Germany | Hospital & Health Care | 1996 | 5 |
|
|
CGI | Canada | Information Technology & Services | 1976 | 4 |
The talent market for Data Science Engineers in Germany, particularly in Hamburg, reveals a challenging landscape for hiring managers. With a notable number of job openings compared to the available talent pool, the ratio indicates that recruiting these specialists can be quite competitive. When juxtaposed with other European countries such as France, Spain, and the Netherlands, Germany's hiring conditions display less favorable ratios, suggesting a tighter market. This trend highlights the critical need for well-strategized recruitment approaches tailored specifically for the tech sector in Germany, Hamburg, positioning hiring managers to better navigate the robust demand for Data Data Science Developers amid the evolving technology landscape.
In the Hamburg job market for Data Data Science Engineering, the seniority distribution reveals a notable concentration in the Mid-Senior level category, accounting for 44% of total job openings. Entry level positions make up 34%, while Associate roles constitute 10%. This distribution underscores the growing demand for experienced professionals in Germany Hamburg's Data Data Science sector.
In the German engineering job market, Full-time positions dominate, accounting for 96% of the available roles. Part-time jobs represent a smaller segment at 4%, while Internship opportunities make up approximately 2% of the employment types. This distribution highlights the stability and reliance on full-time talent as hiring managers navigate the Data Data Science Engineers job market trends in Germany, particularly in cities like Hamburg.
The time to hire distribution for Data Science positions in Germany indicates a complex recruitment landscape. A significant portion, comprising 236 counts, hires take about 10 days, highlighting a pace that hiring managers should be prepared for. The fluctuation in time to hire shows that while many candidates can be brought on board within 30 days, with 210 counts reported, there remains a challenge with hires taking longer—reflecting on the 144 counts for 15 days, and 90 counts for 40 days. This insight underscores the necessity for CTOs and Engineering Managers in the German tech sector to adopt proactive recruitment strategies to stay competitive within the swiftly evolving Data Science job market in Germany, particularly in cities like Hamburg.
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 the German job market for Data Data Science Engineers, Berlin stands out as the primary hub, accounting for 72% of job openings, followed by Munich and Hamburg with 33% and 18% respectively. Notably, Berlin, as the capital, continues to drive significant demand in the tech sector. The accompanying chart illustrates these distribution percentages within the top cities, providing a clearer picture of the opportunities available.
In the Data Data Science job market in Germany, particularly in Hamburg, several technologies have emerged as pivotal in shaping the landscape. Python leads the charge with a significant usage frequency of 8,765, reflecting its dominance in data analysis and machine learning applications. Following closely, SQL is critical for database management and data manipulation, boasting a frequency of 3,046. Machine Learning occupies a vital role with a frequency of 3,522, underscoring its importance in the development of predictive models. Java and JavaScript are also prevalent, with frequencies of 3,073 and 2,058, respectively, highlighting their utility in backend and frontend development environments. These insights are illustrated in the accompanying chart, which provides a visual representation of the most commonly utilized technologies in the Data Data Science sector.
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