Data Science Developer Hiring Trends in Slovenia

This report was last updated on Aug 16, 2025

Bence Gedai

Founder

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.

Key learnings from this report

The Data Data Science job market in Slovenia has seen 25 new roles posted over the last 12 weeks, indicating opportunities for growth despite the closure of 40 positions, highlighting a struggle between talent availability and demand.
Top companies hiring for Data Data Science Engineer roles include Canonical, Axelera AI, and Artificial Intelligence for Digital Humanities, underscoring active recruitment in the tech sector.
Ljubljana dominates the hiring landscape, with 91% of job openings for Data Data Science roles located in the capital, indicating its status as a central hub for tech recruitment in Slovenia.
The median time to hire for Data Engineers in Slovenia stands at 33 days, suggesting an efficient hiring process that remains critical for attracting top talent in a competitive environment.
With a talent pool of approximately 3,800 Data Data Science Developers, hiring in Slovenia remains challenging, necessitating innovative recruitment strategies for CTOs aiming to secure skilled candidates.

Number of roles opened and closed for Data Science Engineers in Slovenia in the last 3 months

Over the past 12 weeks, Slovenia's Data Data Science job market has exhibited notable fluctuations, with a total of 25 new jobs posted. Notably, weeks 24 and 25 saw peaks of 5 and 4 new postings, respectively. However, the hiring landscape has been challenging, as evidenced by the closure of 40 job positions during the same period, indicating a significant gap between new opportunities and positions filled. Unlike other European countries, where the demand for Data Data Science Engineers remains robust, Slovenia's trends highlight a need for innovative recruitment strategies to attract the right talent in this competitive tech sector.

Who else is hiring for data Engineers in Slovenia:

Company name	Country	Industry	Founded	# Job openings
Canonical	United Kingdom	Information Technology & Services	2004	11
Axelera AI	Netherlands	Semiconductors	2021	4
Artificial Intelligence for Digital Humanities (AI4DH)	null	null	null	2
Ruby Labs	United States	Information Technology & Services	2018	2
TSMG Holding	Poland	Outsourcing/offshoring	2018	1
Coley S Home Remodeling	United States of America	Construction	null	1
Henkel	Germany	Mechanical Or Industrial Engineering	1876	1
BMM Testlabs	United States	Gambling & Casinos	1981	1
Oasis	United States	Communications Equipment	2020	1
bunny.net	Slovenia	Information Technology & Services	2015	1

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Talent pool vs job openings for Data Engineers in Slovenia

How competitive it is to hire Data Engineers in Slovenia

The data on the Data Data Science Engineers job market trends in Slovenia indicates a relatively challenging hiring environment when compared with other European nations, such as Germany, Poland, and the Netherlands. Currently, Slovenia has a job openings count of X, with an available talent pool of Y, resulting in a jobs to talent pool ratio of Z. This suggests that for every open position, there are Z potential candidates, indicating that while recruitment is feasible, it may not be straightforward. In contrast, countries like Germany exhibit a more favorable ratio, suggesting easier access to skilled candidates, whereas Poland and the Netherlands present similar challenges as Slovenia, but with varying degrees of availability. As such, hiring managers in Slovenia's tech sector should consider strategic recruitment initiatives and competitive offerings to attract Senior Data Data Science Developers.

Seniority distribution of Data Science Engineer job openings in Slovenia

Seniority Distribution of Data Science Engineering Jobs in Slovenia

The seniority distribution of Data Data Science Engineering jobs in Slovenia reveals significant insights for hiring managers. Mid-Senior level positions make up 46% of the job market, followed by Entry level roles at 30%, and Associate positions at 8%. This distribution highlights the competitive landscape for Senior Data Data Science Developers in Slovenia, indicating a strong need for targeted recruitment strategies aimed at attracting top talent across all experience levels.

Preferred employment type for Engineering roles in Slovenia

In Slovenia, the employment type distribution for engineering roles indicates a strong preference for full-time positions, comprising 89% of the market with 3,455 relevant jobs. Contract roles represent 4% of the employment landscape, totaling 408 opportunities, while part-time positions account for 1% with 152 job listings. This data highlights the prevailing trend towards stable, long-term employment in the Data Data Science Engineer job market in Slovenia.

Time to Hire Distribution for Data in Slovenia

How long does it take to hire Data Engineers

The time to hire distribution for Data jobs in Slovenia reveals critical insights for hiring managers in the tech industry. Notably, the majority of candidates are hired within 30 to 60 days, with 41 applicants taking 30 days and 20 taking 60 days. Furthermore, hiring trends indicate a noticeable drop in candidates hired beyond 60 days, suggesting that companies may face challenges in attracting talent for longer recruitment processes. Understanding this distribution can guide CTOs and engineering managers in refining their recruitment strategies to align with the prevailing market dynamics. For those concerned about the future demand for Data Science Engineers, focusing on quicker hiring timelines may significantly enhance the chances of securing top-tier talent in Slovenia's competitive job market.

Expolore reports from other European Developer talent pools

Insights for hiring Data Engineer Engineers in Denmark

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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Insights for hiring Data Science Engineers in Sweden

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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Insights for hiring Data Engineers in Warsaw

The Data Engineer job market trends in Poland, specifically in Warsaw, present a compelling landscape for hiring managers as they navigate recruitment strategies.

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Most popular cities in Slovenia to hire Data Engineers

Top 5 cities in Slovenia to hire Data Engineers

In Slovenia, the distribution of Data Engineers job openings is notably concentrated in Ljubljana, which accounts for 91% of the total job count. This is followed by Slovenia as a whole, representing 9%, while remote opportunities make up 7% of the market. Notably, cities like Maribor and Škofja Loka contribute lesser percentages, emphasizing Ljubljana's dominance in the Data Data Science job market.

Most sought after technologies in Slovenia for Data Science

Key technologies for Data Science Engineers

In analyzing the current Data Data Science job market trends in Slovenia, it is essential to identify the most commonly used technologies among professionals in the field. The data clearly indicates that Python leads the way with a frequency of 5,846, making it a critical skill for Data Data Science Developers. Following closely behind are Machine Learning at 3,002 and SQL at 2,078, highlighting the importance of these technologies in data management and predictive analytics. Additionally, Java ranks fourth with 1,689 occurrences, while Data Science itself registers 1,671, reflecting the growing focus on data-centric roles. Hiring managers should consider these technologies when evaluating candidates for Data Data Science Engineer roles, as shown in the accompanying chart.

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