Data Analyst Salary in Europe 2026: City-by-City Breakdown

Data analysis has become a core function in companies of nearly every size and sector. The demand for professionals who can extract meaningful insight from data, and communicate it clearly to decision-makers, has grown substantially over the past five years. So have the salaries.

But "data analyst" covers a wide range of actual roles, and the salary variation is significant. A junior analyst running reports in Excel earns very differently to a senior analyst building predictive models in Python or designing experimentation frameworks. Location matters enormously too: a mid-level analyst in London earns roughly twice what their counterpart in Warsaw takes home in gross terms.

This guide covers salary ranges for data analysts across seven major European markets in 2026, broken down by seniority. It also covers the specialisations and skills that drive the largest premiums, and how to benchmark your specific situation.

What "data analyst" means in 2026

The title covers substantial variation. In some companies, it means someone who pulls reports and builds dashboards. In others, it means someone who designs A/B tests, builds ML pipelines, and writes production-quality code. These are not the same job, and they don't pay the same salary.

For this guide, the core definition is: a professional who works primarily with data to answer business questions, produce insights, and support decision-making. The salary ranges represent the typical market for analysts who are technically competent (SQL fluency is a baseline), working at companies where data functions are taken seriously, and whose output materially influences business decisions.

Analysts with ML engineering or data engineering responsibilities are generally at the higher end of the ranges, or are better compared against data scientist and data engineer salary benchmarks.

Salary ranges by city

London

London is the strongest market for data analysts in Europe, driven by the financial services sector, a large and mature e-commerce and tech ecosystem, and high demand for analytically rigorous professionals across sectors.

Junior data analyst (0–2 years experience)

• Typical range: £28,000–£40,000
• Market median: approximately £33,000

Mid-level data analyst (3–6 years experience)

• Typical range: £42,000–£65,000
• Market median: approximately £52,000

Senior data analyst (7+ years, or senior with strong technical depth)

• Typical range: £60,000–£85,000
• Market median: approximately £70,000

London data analysts at financial services companies, investment banks, trading firms, fintech companies, often earn at or above the upper end of these ranges. Analysts at data-mature tech companies (Deliveroo, Monzo, Wise, and similar) typically sit at the mid-point or above. Those at smaller companies or in sectors where data is less strategically central tend toward the lower end.

See the full data analyst salary guide for London →

Amsterdam

Amsterdam has become a strong market for data analysts, driven by Booking.com, Adyen, and a growing cluster of B2B SaaS and data infrastructure companies. The city has developed particular depth in product analytics, growth analytics, and commercial data science.

Junior: €28,000–€40,000 (median ~€33,000) Mid-level: €42,000–€62,000 (median ~€51,000) Senior: €58,000–€80,000 (median ~€68,000)

The 30% tax ruling for qualifying international hires makes Amsterdam effective take-home meaningfully better than the gross figures suggest for non-Dutch nationals. Combined with a lower cost of living than London, Amsterdam offers strong purchasing power for data professionals.

See the full data analyst salary guide for Amsterdam →

Berlin

Berlin's data market reflects its broader tech ecosystem: highly variable, with strong salaries at well-funded companies and meaningfully lower ones at early-stage startups. The city has particular depth in e-commerce (Zalando, About You), food delivery (Delivery Hero), and health tech, all of which are data-intensive sectors.

Junior: €26,000–€38,000 (median ~€31,000) Mid-level: €38,000–€58,000 (median ~€47,000) Senior: €55,000–€75,000 (median ~€63,000)

The gap between well-funded scale-ups and early-stage startups is more visible in Berlin than most European cities. A mid-level analyst at a Series C company might earn €55,000–€60,000; the same profile at a seed-stage startup might earn €38,000–€42,000. Equity is more commonly offered in Berlin, but its value is highly uncertain.

See the full data analyst salary guide for Berlin →

Paris

Paris has developed a strong data culture over the past five years, with companies like Doctolib, ManoMano, and Back Market building data-mature product organisations. Mid-level data analysts typically earn €38,000–€57,000.

Junior: €26,000–€36,000 (median ~€30,000) Mid-level: €38,000–€57,000 (median ~€46,000) Senior: €52,000–€72,000 (median ~€60,000)

French labour law creates strong baseline protections, and the non-salary benefits (healthcare, structured leave entitlements) are often better than equivalent roles in the UK or Netherlands. Variable pay is less common than at US-style tech companies.

Dublin

Dublin's large US tech company presence supports a strong market for data analysts, particularly at companies that are building out analytics functions for their EMEA markets. Mid-level salaries typically fall between €40,000 and €62,000.

Junior: €28,000–€40,000 (median ~€33,000) Mid-level: €40,000–€62,000 (median ~€50,000) Senior: €58,000–€78,000 (median ~€66,000)

The variation between large US tech companies and local Irish companies is significant in Dublin. Analysts working for Google, Meta, or LinkedIn's analytical functions often earn above the ranges listed, while those at Irish-founded companies typically sit at or below the midpoint.

Barcelona and Madrid

Spain offers significantly lower gross salaries for data analysts than the cities above, but also materially lower living costs. The Spanish tech ecosystem has grown substantially, with Barcelona in particular developing a strong data and analytics community.

Junior: €20,000–€28,000 (median ~€23,000) Mid-level: €28,000–€42,000 (median ~€34,000) Senior: €40,000–€58,000 (median ~€47,000)

The remote work dynamic matters particularly here: Spanish analysts working for non-Spanish companies, UK, US, or Northern European employers, often earn significantly above these ranges while living at Spanish costs. This segment of the market has grown materially since 2020.

See the full data analyst salary guide for Barcelona →

Skills that command the biggest premiums

Within any given city and seniority level, the spread between the bottom and top of the data analyst salary range can be 40–60%. The key driver is the depth and relevance of your technical skills.

SQL and data modelling (+8–12% above baseline)

Strong SQL is the baseline expectation for most data analyst roles, but there's a meaningful difference between basic query writing and the ability to design maintainable data models, write performant queries at scale, and work comfortably with dbt or similar transformation frameworks. Analysts who can do the latter consistently earn above those who can't, even with similar total years of experience.

Python for analysis (+10–18%)

The ability to work in Python, beyond just pandas for data manipulation, but including statistical testing, automated reporting, and basic modelling, materially differentiates analysts in the market. Roles that could previously be done in Excel and SQL now increasingly require Python fluency.

A/B testing and experimentation design (+8–14%)

Companies that are serious about data-driven product development rely heavily on well-designed experiments. Analysts who can design statistically rigorous tests, identify threats to validity, and interpret results accurately, rather than just running tests in a third-party tool, are in high demand at product-led companies.

Product analytics specialisation (+10–15%)

Analysts working in product analytics, using tools like Amplitude, Mixpanel, or Looker, understanding funnel analysis, cohort analysis, and behavioural event modelling, command a premium at tech companies where the analyst is working directly in the product decision loop.

Machine learning exposure (+12–20%)

Analysts with meaningful exposure to machine learning, whether building models themselves or working closely with data science teams to inform model design and evaluation, earn above generalist peers. The boundary between "senior data analyst" and "junior data scientist" is blurry, and analysts who can work on either side of it are more valuable.

What doesn't drive your salary as much as you might think

The specific BI tool you use. Tableau, Power BI, Looker, Superset, these tools are learnable in weeks. Companies care about your analytical instincts, your data modelling competency, and your communication skills far more than your specific tool certification. Skills in any of these transfer readily.

Your current salary. Many European countries are moving toward or have already established policies that limit employers' ability to ask about salary history. Your current salary is an anchor on you, not an anchor on what you should be paid. Market rate is the relevant benchmark, not what your current employer chose to pay you.

Job title variations. "Data analyst," "business analyst," "insights analyst," "analytics engineer", these titles vary enormously between companies. What matters is what you actually do, not what it's called.

How to benchmark your specific situation

The ranges above give a useful starting point, but your exact market rate depends on your technical skills, the industry you're in, the type of company you work for, and your experience with specific high-value tools and methods.

A few practical ways to benchmark:

Use our salary checker. Enter your role, location, and years of experience into our free salary tool and see your percentile based on verified public data. If you're below the 40th percentile, there's almost certainly a case to make for a higher salary, either internally or externally.

Pay attention to inbound recruitment messages. Recruiters contact you with roles that pay market rate or above (they need to attract candidates). If inbound messages are regularly referencing salaries above what you currently earn, that's a real market signal.

Compare against active job postings. The EU Pay Transparency Directive, which requires salary range disclosure in job postings, has been coming into force across EU member states. In markets where this applies, active job postings are an increasingly direct benchmark.

Talk to peers. Salary transparency conversations are more normal than they used to be in many data and tech communities. Slack communities, LinkedIn connections, and in-person meetups are all places where these conversations happen.

What to do if you're below market

If your benchmarking shows a gap between your current salary and the market rate for your role and location, the options are:

Internal negotiation, Appropriate if the gap is less than 15% and you have a good relationship with your manager and a track record of impact. Come with data: your market percentile, your contributions over the past 12 months, and a specific number. See our guide on how to ask for a raise.

Testing the external market, Appropriate if the gap is larger, if internal negotiation has stalled, or if you're simply curious. Applying to two or three roles and going through the process gives you real offer data. Even if you don't take any of the jobs, the offers change your negotiating position.

Upskilling to move into a higher-paying bracket, If the gap exists partly because your technical skills are at the lower end of the market, a deliberate upskilling investment (Python, dbt, experimentation methodology) can shift your profile meaningfully within 3–6 months.

The most common mistake is none of the above, accepting the status quo without ever testing whether a better outcome is available. The data analyst market in Europe is active enough that the gap, if it exists, is almost always closable.

Check your salary against the European data analyst market now →