Data Developer Hiring Trends in Austria

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 current Data Engineers job market in Austria exhibits a competitive landscape, highlighted by fluctuating weekly job postings that peaked at 83 openings, with significant closures often exceeding new postings.
A total talent pool of positions emphasizes that 39% are entry-level, indicating a strong demand for junior talent, while both mid-senior level and associate roles also attract considerable interest from employers.
Leading hiring companies, such as Frequentis with 12 openings, eurofunk Kappacher GmbH with 10, and Raiffeisen Software GmbH with 6, underscore the active recruitment environment in Austria's tech sector.
Vienna dominates the job distribution with 82% of the openings, followed by Linz and Graz, reinforcing the importance of location-based strategy in recruitment efforts for data roles.
The median time to hire Data Engineers in Austria is currently 34 days, suggesting a pressing need for CTOs and Engineering Managers to implement efficient recruitment strategies to quickly secure qualified candidates.

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

In recent weeks, the Data Engineer job market in Austria has shown fluctuating activity, with weekly job postings peaking at 83 openings in week 22 and experiencing a low of 26 in week 28. Notably, the number of closed jobs has remained significant, peaking at 87 in week 25. This indicates a competitive landscape for Data Developer opportunities in Austria, with the number of jobs closed often surpassing new openings during certain weeks. Compared to other European countries, these trends reflect a stable yet challenging environment for recruiting Data Engineers, necessitating adaptive recruitment strategies for CTOs to meet the future demand for Data Engineers in Austria's tech sector.

Who else is hiring for data Engineers in Austria:

Company name	Country	Industry	Founded	# Job openings
TieTalent	Switzerland	Information Technology & Services	2017	27
Canonical	United Kingdom	Information Technology & Services	2004	25
TELUS Digital	Canada	Information Technology & Services	2005	15
Frequentis	Austria	Information Technology & Services	1947	12
eurofunk Kappacher GmbH	Austria	Information Technology & Services	1969	10
Porsche Holding	Austria	Wholesale	1947	8
Bending Spoons	Italy	Information Technology & Services	2013	7
Liebherr Group	Germany	Machinery	1949	7
COSMO CONSULT	Germany	Information Technology & Services	1996	7
Raiffeisen Software GmbH	Austria	Information Technology & Services	2015	6

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Talent pool vs job openings for Data Engineers in Austria

How competitive it is to hire Data Engineers in Austria

The Data Engineers job market in Austria presents a notable challenge for hiring managers within the tech sector. With a count of job openings significantly outpacing the available talent pool, Austria's ratio indicates a competitive landscape. For instance, when compared to Germany, which has a more favorable ratio, and the Netherlands and France, where job abundance aligns more closely with talent availability, Austria poses a more difficult recruitment scenario. As CTOs and Engineering Managers strategize for the recruitment of Data Engineers, understanding these dynamics will be essential for effective hiring strategies in this competitive environment.

Seniority distribution of Data Engineer job openings in Austria

Seniority Distribution of Data Engineering Jobs in Austria

In Austria's Data Engineering job market, the majority of positions are distributed across three primary seniority levels. Entry-level roles account for 39% of the market, closely followed by Mid-Senior level positions at 36%. Associate roles make up 13%, highlighting a significant demand for talent at both the entry and mid-career stages.

Preferred employment type for Engineering roles in Austria

In the Austrian tech sector, the predominant employment type for engineering roles is full-time positions, accounting for 95% of the job market. Part-time roles represent 4%, while contract positions make up 4% as well. This distribution highlights a robust demand for full-time Data Engineers in Austria, underscoring the importance of strategic recruitment efforts aimed at securing top talent in this competitive landscape.

Time to Hire Distribution for Data in Austria

How long does it take to hire Data Engineers

The time to hire for Data Engineer positions in Austria reveals significant insights into the hiring landscape. A notable 311 roles are filled within 30 days, suggesting a robust demand for talent in this timeframe. As the hiring duration extends, the distribution indicates diminishing counts, with only 50 positions taking 45 days and 7 beyond 100 days. The predominant hiring window appears to be between 25 and 35 days, underscoring the urgency for CTOs and hiring managers to adopt effective recruitment strategies to secure top candidates swiftly in Austria's competitive tech sector.

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Most popular cities in Austria to hire Data Engineers

Top 5 cities in Austria to hire Data Engineers

In Austria, the location distribution for Data Engineers job openings reveals a significant concentration in Vienna, which accounts for 82% of the total job postings. The second city, Linz, represents 12% of the job market, while Graz follows closely with 12%, emphasizing the capital's dominance in the Data job market in Austria. For a comprehensive overview, please refer to the accompanying chart.

Most sought after technologies in Austria for Data

Key technologies for Data Engineers

The Data job market in Austria is currently characterized by a significant emphasis on several key technologies, as depicted in the accompanying chart. Python leads the pack with its usage frequency reaching 8,339, showcasing its versatility and importance for Data Engineers. SQL follows closely, used 7,824 times, indicating its critical role in data management and querying. Additionally, Data Analysis technologies are employed 2,285 times, highlighting a growing focus on deriving insights from data. Tools related to Data Engineering are also critical, with a notable frequency of 3,748, underscoring the demand for structured data solutions. Lastly, ETL processes are pivotal, appearing 3,112 times, reflecting the vital need for efficient data integration in the hiring strategies for CTOs in Austria's tech sector.

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