Average Salaries ($K)
Munich 2020-2024
Data Salary review
Munich
2020 - 2024
- 24% Average Cost Of Living Rise
- #13/23 Cheapest City To Live
- 20% Average Salary Rise
- #8/23 Salary Growth - All Roles
- #21/23 Salary Growth For Heads Of Data
- #11/23 Salary Growth For Data Engineers
- #4/23 Salary Growth For Data Analyst
- #11/23 Salary Growth For Data Scientists
Overview
Munich has emerged as a major European tech hub, particularly for data roles, thanks to its strong industrial base and growing digital economy. Traditional powerhouses like BMW, Siemens, and Allianz are increasingly investing in AI, big data, and automation, creating demand for data scientists, analysts, and engineers. The city also has a thriving fintech and healthtech scene, with startups and scale-ups driving innovation. While multinational giants like Google and Microsoft have expanded their presence, mid-sized companies and startups offer alternative career paths creating a very balanced picture.
In recent years, the data job market in Munich has become more competitive, especially for junior roles, as more candidates flood the field. Companies now prioritise hands-on experience and industry-specific knowledge, making it harder to break in without strong credentials. The high cost of living is another challenge, with salaries for data roles sometimes struggling to keep pace with rising rents. That said, for mid-career professionals, Munich offers exciting opportunities, particularly in industries undergoing digital transformation. While entry-level candidates may face hurdles, those with experience will find a city that values data expertise, just be prepared for corporate bureaucracy in traditional sectors.
Heads Of Data
Head of Data roles in Munich are in high demand, but they come with steep requirements. Many companies are looking for experienced leaders who can drive data strategy, build teams, and integrate analytics into business decision-making. However, unlike in some U.S. tech hubs where a strong technical background alone can land you a leadership role, Munich employers often expect candidates to have a mix of deep industry knowledge, managerial experience, and a strong grasp of business strategy. Many Head of Data roles sit at the intersection of technology and traditional corporate structures, meaning you will often need to navigate bureaucracy while driving innovation.
Given the presence of both multinational giants and emerging startups, there is a mix of opportunities, but standing out requires more than just strong machine learning or engineering skills, you need to demonstrate impact, whether through optimising supply chains, reducing risk in insurance models, or leading a data transformation project. Munich’s professional scene is well-connected, and personal referrals can carry significant weight in hiring decisions.Munich’s market tends to favour candidates with corporate or enterprise experience.
While Munich can be an excellent place to hold a Head of Data role, it can also be challenging, especially in older industries resistant to change. Wages have not been growing with a 8.33% at intermediate level and 8.69% at expert level both falling behind inflation when comparing 2020 and 2024 salaries, and ranking Munich #21/23 for wage growth in our review.
Average Salaries ($K) By Experience
Data Engineers
Data engineering roles in Munich are in high demand, driven by the city’s strong industrial base and the increasing adoption of AI, cloud computing, and big data technologies. Large enterprises like BMW, Siemens, and Allianz rely heavily on scalable data infrastructure, while startups and mid-sized companies are rapidly building out their data capabilities. The role typically involves designing and maintaining data pipelines, optimising ETL processes, and working with cloud platforms like AWS, Azure, or GCP. Unlike in some other tech hubs, where startups dominate the hiring scene, Munich offers a mix of opportunities across corporate giants, consulting firms, and high-growth scale-ups.
Breaking into data engineering in Munich requires a strong foundation in software development, cloud architecture, and distributed systems. While a background in computer science or a related field helps, many professionals transition from software engineering or data science roles. Munich employers tend to value practical experience with enterprise-grade tools like Snowflake, Kafka, and Databricks. Certifications in cloud platforms and strong SQL and Python skills can help candidates stand out, but industry-specific expertise (e.g. automotive IoT data, financial risk modelling) can be a key differentiator.
The job market for data engineers in Munich is competitive but still offers good entry points for those with the right skill set. Senior roles, in particular, are highly sought after, as many companies struggle to find experienced professionals who can architect and scale complex data infrastructures. We see high demand post-pandemic with average salaries rising by 57.14% at beginner level, 31.57% at intermediate level and 11.53% at expert level, but the next year demand slumps and there is very tight banding between all experience levels, with a market correction in 2024. While Munich provides stable, well-paying opportunities, some engineers may find the work less cutting-edge compared to Berlin or London, where more startups experiment with bleeding-edge tech. That said, for those who value job security, high-impact projects in established industries, and the chance to work on large-scale data systems, Munich remains an excellent place to build a data engineering career. Munich ranked #11/23 for wage growth comparing 2020 and 2024 salaries.
Average Salaries ($K) By Experience
Data Analysts
Data analyst roles in Munich are widely available, especially within the city’s dominant industries like automotive, finance, insurance, and manufacturing. Companies like BMW, Allianz, and Munich Re rely heavily on data analysts to interpret business metrics, optimise operations, and drive data-driven decision-making. Additionally, consulting firms such as McKinsey, BCG, and Accenture have a strong presence in the city, hiring analysts for client-facing roles. Compared to other tech hubs, Munich’s data analyst jobs lean more toward business intelligence, dashboarding, and reporting rather than advanced statistical modelling or machine learning.
Breaking into data analytics in Munich typically requires strong SQL skills, experience with visualisation tools like Power BI or Tableau, and proficiency in Python or R for data manipulation. While technical expertise is important, domain knowledge in sectors like automotive, finance, or supply chain can set candidates apart. Unlike in London or Silicon Valley, where data analysts often work in highly product-driven roles within tech firms, Munich’s market is more business-focused, with many positions embedded in traditional industries.
The competition for data analyst roles in Munich has intensified in recent years, particularly for entry-level positions, as many candidates enter the field from business, economics, or STEM backgrounds. While senior roles with specialisation in areas like pricing analytics, fraud detection, or marketing attribution remain in demand, junior candidates may struggle to stand out without relevant work experience or industry connections.
As with many other tech hubs, we see a huge 33.33% average wage growth between 2021 and 2022, followed by stagnation since. This rapid growth in 2022 is the major contributing factor in Munich ranking #4/23 as our ranking takes into account 2020 and 2024 salaries.
Average Salaries ($K) By Experience
Data Scientists
The data science job market in Munich is oversaturated with junior candidates, making it tough to break in unless you have real-world experience, strong engineering skills, and domain expertise. Many companies now expect data scientists to be full-stack, handling everything from ML models to data engineering and cloud deployment, often for less pay than specialised software engineers. On top of that, some roles labeled “Data Scientist” are really just glorified BI jobs, focusing on dashboards and reporting rather than serious machine learning. At big corporations like BMW, Allianz, and Siemens, you will likely spend a lot of time fighting bureaucracy just to get access to usable data, while executives remain skeptical of AI-driven decision-making. In startups, it is the opposite, you may be expected to do everything data-related with little structure or understanding of what a data team actually needs. There is however good news for more experienced candidates with a noticeable 42.85% gap between intermediate and expert level highlighting just how in-demand those roles are. If you are an experienced data scientist with strong technical and business skills, Munich can still be a great place to work on large-scale, industry-driven problems. But if you are looking for rapid innovation, cutting-edge AI research, or a fast-track career path, Berlin, London, or the U.S. might be better bets.
Average Salaries ($K) By Experience
Hiring Data Roles For Munich Companies
Munich has a large talent pool for data professionals, but the availability and quality of candidates vary significantly by role. Junior data analysts and data scientists are abundant, often coming from local universities or bootcamps, but many lack real-world experience beyond coursework and personal projects. In contrast, senior data scientists, data engineers, and experienced Head of Data candidates are much harder to find. The market has shifted towards data engineering and MLOps, with companies realising that strong infrastructure is a prerequisite for advanced analytics. Hiring for these roles is competitive and expensive, as top candidates are often already employed at BMW, Allianz, or large consulting firms. Salaries in Munich are high compared to other German cities but lower than London or the U.S., though the rising cost of living makes it harder to attract international talent without premium compensation packages.
Hiring a data agency like 173tech makes sense when a company needs immediate expertise but does not have the resources or time to build an in-house team. This is especially relevant for startups and mid-sized firms that lack the budget for a full data department but need to implement dashboards, predictive models, or data pipelines quickly. It is also a smart choice when internal teams are too focused on business-as-usual tasks to handle a one-time project, data migration, or growth initiatives. For businesses that are just starting to leverage data, an agency can help set up scalable infrastructure and define a proper data strategy before making long-term hires. However, for companies that rely heavily on data for core operations, investing in a strong in-house team is usually the best long-term strategy.
173tech Direct Comparison
- Head Of Data (5+ yrs) $250k
- Data Engineer (5+ yrs) $135k
- Data Engineer (0-3 yrs) $80k
- Data Analyst (3-5 yrs) $85k
- $550k per yr + Tax + Pension + Holidays
- Candice (15+ yrs) Ruben (8+ yrs) Oliver (10+ yrs)
- Adrian (15+ yrs)
- Oscar (2+ yrs)
- Emeric (3+ yrs) Mai (4+ yrs) Noel (2+ yrs) Amy (2+ yrs)
- $240k
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