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 recent weeks, the Data Engineer job market in Switzerland Zug has shown a fluctuating yet intriguing trend. Over the last 12 weeks, there were notable peaks, particularly in week 11 with 11 new positions, contrasting sharply with lows of just 1 in weeks 14 and 18. However, the market has been tempered by a significant closure of jobs, with 11 positions closed in week 14 and consistent closures averaging between 3 to 7 roles each week. This pattern reveals a competitive landscape, as the hiring for Data Engineers continues to be challenged by the rate of job closures, highlighting the need for strategic recruitment approaches. Comparatively, the situation in Zug is slightly more volatile than other tech roles across Europe, suggesting a unique dynamic in the Data job market within the region.
| Company name | Country | Industry | Founded | # Job openings | |
|---|---|---|---|---|---|
|
TieTalent | Switzerland | Information Technology & Services | 2017 | 30 |
|
JobCourier | Switzerland | Human Resources | null | 30 |
|
Outlier | United States | Information Technology & Services | 2023 | 7 |
|
Hays | United Kingdom | Staffing & Recruiting | 1968 | 7 |
|
ti&m | Switzerland | Information Technology & Services | 2005 | 7 |
|
Swisscom | Switzerland | Information Technology & Services | 1998 | 6 |
|
Deloitte | United States | Management Consulting | 1845 | 6 |
|
|
University of Bern | null | null | null | 5 |
|
ELCA Group | Switzerland | Information Technology & Services | 1968 | 5 |
|
Sonar | Switzerland | Information Technology & Services | 2008 | 4 |
The data job market in Switzerland, particularly in Zug, reveals a competitive landscape for Data Engineers. With a current count of job openings juxtaposed against the available talent pool, the hiring ratio indicates that recruitment may pose challenges in Switzerland, especially when compared to countries like Germany, where the talent pool is more robust relative to job opportunities, and the Netherlands, which demonstrates a similar pattern. In contrast, Poland shows a more favorable jobs-to-talent ratio, suggesting a less competitive hiring environment. Consequently, CTOs and hiring managers in Switzerland must adopt tailored recruitment strategies to attract the right candidates amid a tightening talent pool, as future demand for Data Engineers continues to rise across Europe.
In Switzerland Zug's Data Engineering job market, the seniority distribution highlights a significant emphasis on Mid-Senior level positions, accounting for 43% of available roles. Entry level jobs represent 35% of the market, while Associate positions make up 11%. This distribution suggests a strong demand for experienced professionals, alongside opportunities for entry-level talent, crucial for hiring managers looking to strategize their recruitment efforts.
In Switzerland, the employment type distribution for engineering roles reveals a significant preference for full-time positions, accounting for 92% of the job market. Part-time roles follow, representing 6% of the total, while contract positions make up 1% of the market. This data highlights the strong demand for stable, long-term employment opportunities within the engineering sector in Switzerland, particularly in Zug.
The time to hire distribution for Data jobs in Switzerland reveals critical insights for hiring managers in Zug and the broader tech sector. A significant portion of hires, approximately 31.6%, fall within 30 to 35 days, indicating an optimal hiring window for attracting top Data Engineers. However, there is a noticeable increase in candidates taking up to 70 days, with a cumulative count of 60, reflecting a competitive landscape for Data job market in Switzerland Zug. To effectively navigate this environment, CTOs and recruiters should consider adjusting their recruitment strategies to align with these trends, focusing on expediting the hiring process to secure skilled Data Developer opportunities.
The current talent pool for Data Data Science Engineers in Estonia, particularly in Tartu, is competitive, with significant challenges noted in the hiring landscape. In the past three months, Tartu saw fluctuations in job openings, with a total of three positions peaking in one week and a concerning number of closures indicating a discerning hiring environment.
View ReportThe Data Engineers job market trends in Switzerland Zug indicate a fluctuating yet competitive environment, highlighted by the closure of 11 positions in a single week, necessitating strategic recruitment approaches.
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The Data Engineer job market in Romania's Ilfov region is characterized by fluctuating activity, with a peak of 9 new job postings in week 14, highlighting the need for robust recruitment strategies.
View ReportIn Switzerland, the data engineer job market is predominantly concentrated in Zurich, accounting for 66% of the total job openings. Following Zurich, Bern and Geneva represent 17% and 17% of the opportunities, respectively. This distribution highlights Zurich as the pivotal city for data engineer recruitment in Switzerland, as illustrated in the attached chart.
In the burgeoning Data Engineers job market trends in Switzerland Zug, several key technologies are prominently shaping the landscape. Python stands out as the leading programming language, with a frequency of 12,052, demonstrating its essential role in data-related tasks. SQL closely follows with 10,595 counts, confirming its importance in database management and data retrieval. Additionally, the increasing reliance on ETL (Extract, Transform, Load) processes is reflected in its frequency of 4,020, which is crucial for data integration. Furthermore, AWS and Azure are noteworthy technologies, commonly employed for cloud services, with frequencies of 2,790 and 2,695 respectively. These findings are illustrated in the accompanying chart, providing visual insights into the prevalent technologies for Data jobs in the region.
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