Data Analyst Salary UK 2026: Ranges by Level & Region

By James Cotton, Founder of iO-Sphere

In short

The median gross annual salary for a data analyst in the UK is £38,107, according to the ONS Annual Survey of Hours and Earnings (ASHE Table 14, 2025 provisional). Entry-level roles typically start around the 25th percentile (£30,000); the median for mid-level analysts is £38,107; the 75th percentile — where senior roles begin — is £46,152 (ONS ASHE 2025 provisional, SOC 3544). London and financial-services roles push above these benchmarks; public sector and retail roles tend to sit below. Technical skills — particularly SQL, Python, and Power BI — are consistently associated with higher advertised salaries, though the exact premium varies by employer and role. A funded programme on the job, such as a Level 4 Data Analyst programme under the ST0118 standard, lets you build those skills without sacrificing income during training.

Key figures at a glance

Median UK data analyst salary (ONS ASHE, 2025 provisional, SOC 3544): £38,107
25th percentile — lower half of middle earners (ONS ASHE, 2025 provisional): £30,000
75th percentile — upper half of middle earners (ONS ASHE, 2025 provisional): £46,152
90th percentile — top earners (ONS ASHE, 2025 provisional): Check the current ONS ASHE Table 14 dataset directly for the latest SOC 3544 90th percentile figure — it is published in the same table and is the most reliable upper-band benchmark available.
Source: ASHE Table 14: Occupation (4-digit SOC 2020), Office for National Statistics, published 23 October 2025

These are gross annual pay figures for employees in SOC 3544 (data analysts) across the UK. Figures are 2025 provisional; ONS typically revises provisionals marginally in the following year.

What is a data analyst?

A data analyst collects, cleans, and interprets structured data to help organisations make better decisions — turning raw figures into clear findings that non-technical stakeholders can act on.

Data analyst vs data scientist — what's the difference?

A data analyst works primarily with existing data to answer defined business questions; a data scientist builds predictive models and statistical algorithms, typically requiring a stronger mathematical and programming background. The ONS classifies data analysts under SOC 3544 (associate professional level); there is no dedicated ONS occupation code for data scientists, so the ONS does not publish a separate salary median for the role. Industry salary surveys consistently report higher pay for data scientists, reflecting the stronger mathematical and programming demands. If your goal is data science, the honest advice is to use an analyst role as a foundation, then pursue a specialist qualification or postgraduate conversion. This page covers the analyst role and its salary trajectory.

Demand and job market for UK data analysts

The structural case for data analyst roles rests on employer need for applied data skills outpacing the supply of people who hold them. ONS Labour Force Survey and NOMIS employment data track the size of SOC 3544 (data analysts) over time; for the current employed population figure, search for SOC 3544 on ONS NOMIS. The DfE's annual Employer Skills Survey consistently identifies data and digital skills gaps as among the most commonly reported by UK employers across sectors, which underlies continued apprenticeship investment in data routes.

Short-term vacancy counts fluctuate with hiring freezes and macroeconomic conditions. The durable signal is that organisations in finance, technology, health, and retail have all materially expanded their data teams over the past decade, and that expansion has not reversed. Entry-level supply (bootcamp graduates, self-taught career changers) has grown too — which is why demonstrable applied skill at interview matters more than it did five years ago. A credential alone is no longer sufficient differentiation.

UK data analyst salary by experience level

What does an entry-level data analyst earn?

Entry-level data analyst roles in the UK typically sit at or below the 25th percentile of the ONS distribution — around £30,000 gross annually for most roles outside London and financial services. The ONS ASHE 2025 provisional data shows the 25th percentile for SOC 3544 at £30,000. Employer size and sector push the actual figure up or down from there.

What moves an entry-level offer higher? Demonstrable skills on real data — a portfolio project using SQL or a dashboard built in Power BI or Tableau — consistently outperforms a certificate alone. Employers hiring at entry level are largely hiring for evidence of applied ability, not credentials.

What does a mid-level data analyst earn?

The ONS median — £38,107 — is the most defensible single benchmark for a mid-level UK data analyst with two to five years' experience. At this level, you're expected to work with less supervision, own an analysis end-to-end, and translate findings for a non-technical audience. The middle 50% of earners sit between £30,000 and £46,152, per the ONS ASHE 2025 provisional — so a credible mid-career band is roughly £35,000–£46,000 depending on sector and location.

What does a senior data analyst earn?

The 75th percentile in the ONS data is £46,152. Senior analysts — those owning complex analytical workstreams, mentoring junior colleagues, or working in higher-paying sectors like finance or technology — typically sit above this threshold. ONS ASHE Table 14 also publishes a 90th percentile column for SOC 3544; refer to the ONS ASHE Table 14 dataset directly for the current upper-band figure, which is the most reliable published benchmark for top-decile analyst earnings. London and financial-services roles cluster toward and above the 90th percentile nationally; advertised figures on job boards tend to run higher still, partly because vacancies concentrate in specialist roles and partly because employers post ceiling figures.

One caveat worth stating plainly: ONS ASHE measures actual earnings of employees in post, not advertised salaries. Use the ONS numbers as your floor benchmarks, not ceilings.

How location affects your data analyst salary

What does a data analyst earn in London vs the rest of the UK?

The ONS ASHE national median covers all UK regions, so London's higher pay pulls the overall figure upward. The national picture — £38,107 median, £30,000–£46,152 interquartile range — understates what you'd typically earn in London and overstates what's typical in many regional markets.

ONS publishes regional earnings tables alongside ASHE. For the current London vs regional split for SOC 3544, refer directly to the ONS ASHE Table 14 dataset for the most precise up-to-date comparison. London roles consistently attract a meaningful premium above equivalent regional roles; for the current figure, the ONS ASHE regional breakdown is the authoritative source. The general pattern, consistent across years and reinforced by advertised salary data, is that London roles command more — reflecting both the concentration of financial and technology employers and London's cost-of-living weighting in total compensation.

Outside London, salaries in the South East and Scotland's tech centres (Edinburgh, Glasgow) tend to run closer to the national median. The North of England, Wales, and Northern Ireland often sit below it, though remote-first roles have compressed the gap for positions where in-office presence isn't required.

Does remote working change the regional picture?

Remote and hybrid roles have made geography less deterministic than it was five years ago, but the London premium hasn't fully evaporated. Many London-headquartered employers still set salaries against London cost-of-living benchmarks even for remote hires; others apply regional pay frameworks that reduce the premium for non-London employees. If you're evaluating a remote role, establish which salary-setting approach the employer uses — the difference can be substantial.

Industry and sector pay differences for data analysts

Which sectors pay data analysts the most?

The ONS ASHE national figure covers data analysts across all industries. Sector-level breakdowns by occupation at this level of granularity require the ONS ASHE cross-tabulation tables — check the current ONS ASHE Table 14 dataset for the latest split. The consistent picture from advertised salary data and recruiter benchmarks is:

Financial services and insurance — typically the highest-paying sector for data analysts. Banks, insurers, and asset managers need analysts who can work with regulatory data, risk models, and customer-behaviour data. Roles in this sector routinely sit at or above the 75th percentile nationally.
Technology and software — competitive with finance at senior levels; particularly strong for analysts who combine SQL/Python with product analytics or experimentation skills. Start-ups may pay equity-heavy packages that complicate straight salary comparisons.
Retail, e-commerce, and FMCG — broadly in line with the national median for most roles. Analysts working on trading or pricing functions in large retailers can approach finance-sector levels.
Public sector and NHS — typically below the private-sector median, but with stronger pension contributions, job security, and work-life balance as offsetting factors. Roles are assessed against national pay frameworks (Agenda for Change in health, civil-service pay bands elsewhere) that cap progression speed.
Consultancy — variable. Smaller specialist firms may pay above median; larger generalist consultancies often align to their own internal banding.

The honest summary: if maximising salary is your primary goal, financial services in London is the most reliable route to the upper quartile. If stability, pension, and public-service mission matter more, the public sector is worth the pay trade-off — and the work is often genuinely interesting.

How apprenticeship training compares to bootcamps and self-study on salary outcomes

Does your training route affect your starting salary as a data analyst?

No published, methodologically sound UK study directly compares the starting salaries of apprenticeship-trained vs bootcamp-trained vs self-taught data analysts holding equivalent roles. Any specific percentage uplift claimed for one route over another is extrapolating beyond the available evidence.

What the evidence does show is the national earning distribution once in role (the ONS data above), and what the training routes structurally imply for income during training:

Work-embedded training (such as a funded Level 4 Data Analyst programme): You are employed and earning throughout. Training happens on the job, building skills on real data in a real organisation. There is no income gap. You arrive at the end of the programme with applied, employer-validated experience — not just a certificate. Skills built by doing, in context, transfer more reliably than skills built in a classroom or by watching recorded sessions — and employers at interview can usually tell the difference.

Bootcamps: Typically three to six months, full-time or intensive part-time. Many learners take time off work or accept reduced income during the cohort. The DfE-funded Skills Bootcamp route (including iO-Sphere's own bootcamp programme) mitigates this for eligible learners — but the income interruption still applies for full-time formats. Bootcamp graduates frequently enter at the lower end of the entry-level band and build from there.

Self-study: No income cost if you study alongside employment, but typically slower progress, lower accountability, and — harder to evidence applied skill at interview without project work on real data.

The structural advantage of a funded employer-sponsored programme is not that it produces a higher starting salary than a bootcamp. It's that you earn while learning, build skills in a real business context, and avoid the savings drawdown or debt that intensive bootcamps can require. Whether that translates into a salary premium over time depends on the individual, the employer, and the sector — not the training format alone.

For a fuller comparison of routes, see our guide: apprenticeship vs bootcamp — which is right for you?

What skills push your data analyst salary higher?

Which technical skills are most associated with higher data analyst pay?

The consistent signal from UK job postings and recruiter salary guides is that certain technical skills command a premium at both entry and mid-level — though the magnitude varies by employer and role, and no single verified study pins an exact percentage to each skill.

SQL is non-negotiable at every level. Roles that require advanced SQL — window functions, complex joins, query optimisation — consistently attract higher bands than those limited to basic querying. If you're learning one thing first, SQL is the answer; see our post on SQL vs Python — which to learn first for a fuller comparison.

Python (for data analysis) opens a second tier of roles. Analysts who can use pandas, write reusable scripts, and automate reporting are more valuable to engineering-adjacent teams and appear more frequently in the higher advertised ranges. Python doesn't replace SQL; the combination is stronger than either alone.

Power BI / Tableau — data visualisation tools are embedded in most analyst job descriptions. Proficiency moves you from "can produce a report" to "can own the reporting layer," which matters for progression into lead analyst or analytics manager roles.

Cloud data platform literacy (Snowflake, BigQuery, Databricks) is an emerging differentiator. Junior-to-mid analysts who can work in these environments are increasingly preferred over those limited to on-premise tools.

Domain knowledge matters more than most training resources admit. An analyst who understands the commercial logic of the sector they work in — how a bank earns revenue, how a retailer's supply chain works, what a public-sector commissioner is trying to optimise — is considerably more valuable than one who treats data as purely technical artefacts. This is harder to teach in a classroom and easier to build through embedded, on-the-job practice.

For current data on advertised salary by skill keyword, Reed's annual Salary Guide and Lightcast's job-posting analytics are the most granular public sources — search for SOC 3544 or "data analyst" with skill filters applied.

Which soft skills affect data analyst salary progression?

Communication — specifically the ability to translate a finding into a recommendation that a decision-maker can act on — is the single most-cited differentiator in analyst performance reviews. Analysts who grow into senior or lead roles almost always get there because they bridged the gap between analysis and decision-making, not just because they knew more tools.

Stakeholder management and the ability to scope an analytical question well (rather than just execute one) are similarly valued at mid-to-senior level. These skills are built through practice in real organisational settings, not through course content alone.

Data analyst salary trajectory: where the role leads next

What are the typical career progression paths from data analyst?

The most common progressions from a data analyst role in the UK are:

Senior Data Analyst / Lead Analyst — deeper technical ownership, team leadership, and direct stakeholder management. This is typically the first promotion step and sits above the 75th percentile in the ONS distribution (£46,152+).
Analytics Manager / Head of Analytics — managing a team of analysts, owning the analytics function for a business unit, and setting analytical standards. Salary typically reaches well above the ONS data-analyst distribution; this role blends technical credibility with management.
Data Engineer — a technically deeper path focused on building the data pipelines and infrastructure that analysts rely on. Data engineers typically earn above the data analyst median at equivalent experience. The ONS does not publish a dedicated occupation code for data engineers — they fall across broader IT and software-professional classifications — but salary survey data consistently places them higher at mid-level, with the exact gap varying by sector. iO-Sphere delivers a Level 5 Data Engineering programme for analysts ready to move in this direction.
Business Intelligence (BI) Developer / BI Analyst — specialist track focused on reporting infrastructure, dashboarding, and enterprise BI tooling.
Data Scientist — the most frequently cited "next step" in articles about data analyst careers, and worth addressing honestly. The data scientist role requires stronger statistical and machine-learning foundations than most data analyst roles, and often a postgraduate qualification or specialist study beyond Level 4. Treat it as a realistic medium-term target rather than an immediate next step. iO-Sphere doesn't currently deliver a data science programme, so if that's your target, you'll want to explore specialist routes beyond our offering.
Product Analyst / Growth Analyst — hybrid roles in technology companies that blend data analysis with product thinking. Highly paid at senior levels in tech and start-up environments.

The ONS ASHE data for SOC 3544 captures the data analyst occupation specifically. As you move into management or engineering roles, you exit that SOC code and enter differently classified and typically better-paid occupations. The £38,107 median is a floor reference, not a ceiling.

How to get started as a data analyst in the UK

What's the fastest route into a data analyst role?

The answer depends on your starting point.

If you're currently employed in a role that involves any data work — reporting, Excel, business administration — a funded Level 4 programme on the job is likely the most efficient route. You build skills in your existing context, your employer bears most or all of the training cost, and you emerge with a qualification and demonstrated experience in a real business. The Advanced Data & AI programme at iO-Sphere runs against the Data Analyst standard (ST0118, v1.1, approved for delivery) and is designed for exactly this situation. Read more about the route on our how to become a data analyst guide.

If you're changing careers from outside data entirely, a skills bootcamp or intensive programme can compress the transition to three to six months — though you'll need to invest in building a portfolio of applied work to make entry-level applications competitive. iO-Sphere has trained over 900 learners in data and AI since 2022 through bootcamps and funded qualifications.

If you're still at the research stage, the most useful next step is to look at actual job postings for entry-level data analyst roles in your sector and note what's consistently asked for. SQL is almost always there. Python appears frequently. Domain knowledge of the sector you want to enter is underrated. Build those three things, and the qualification layer becomes easier to frame.

Who is this path NOT right for?

An honest guide earns more trust — and makes better decisions — by saying when a path is wrong for someone:

If you want to build machine-learning models from scratch, a data analyst route alone won't get you there. You'd need data science training on top.
If you need to be earning full-time income immediately and your employer won't sponsor training, an intensive bootcamp without income may create financial pressure that undermines the learning. Self-study alongside employment is slower but doesn't create that pressure.
If you're looking at Level 6 or Level 7 qualifications, those sit outside what iO-Sphere delivers. Our Level 4 Advanced Data & AI programme is an excellent foundation — but we'd rather point you to the right destination than overstate our scope.

For career-changers specifically, our post on how career changers succeed in data addresses the common sticking points more directly.

Frequently asked questions

What is the average data analyst salary in the UK in 2025?

The median gross annual salary for a data analyst in the UK is £38,107, according to the ONS Annual Survey of Hours and Earnings (ASHE Table 14, 2025 provisional), covering SOC 3544. The middle 50% of earners fall between £30,000 (25th percentile) and £46,152 (75th percentile). These are actual earnings in post — advertised salaries on job boards typically run higher.

How much do entry-level data analysts earn in the UK?

Entry-level data analyst salaries in the UK typically sit at or below the 25th percentile of the ONS distribution — around £30,000 gross annually for most roles outside London and financial services. Sector, employer size, and your ability to demonstrate applied skills at interview all affect where your first offer lands within that range.

Is a data analyst salary higher in London?

Yes. The ONS ASHE national median reflects all UK regions. London roles consistently attract a meaningful premium above equivalent regional roles — for the current London-specific figure, refer to the regional breakdowns in the ONS ASHE Table 14 dataset, which publishes regional tables alongside the national figures.

Does SQL or Python knowledge increase a data analyst's salary?

Yes, consistently — though the exact premium varies by employer, sector, and role level. SQL proficiency is essentially table stakes for most analyst roles; advanced SQL (complex joins, window functions, query optimisation) commands more than basic querying. Python expands the range of roles available and is associated with higher bands, particularly in technology and product-analytics environments. The combination of SQL and Python is stronger than either alone. See our post on SQL vs Python — which to learn first.

How does a data analyst salary compare to a data scientist salary in the UK?

There is no dedicated ONS occupation code for data scientists, so the ONS does not publish a separate median for the role — unlike data analysts, who are classified under SOC 3544. Industry salary surveys consistently report that data scientists earn more at equivalent experience, with higher entry floors and upper-band ceilings. The roles differ in scope: analysts work primarily with existing data to answer business questions; scientists build predictive models and run statistical research, usually requiring stronger mathematical foundations. A data analyst role is a reasonable foundation toward data science — but be clear-eyed that it's a stepping stone, not a direct equivalent.

Which industry pays data analysts the most?

Financial services and insurance consistently appear at the top of the advertised salary range for data analysts in the UK, followed closely by technology companies. Public sector and retail roles tend to sit at or below the national median. For precise sector-level figures, the ONS ASHE cross-tabulation tables (available at the ONS dataset page) give the most reliable current benchmark.

What qualifications or entry requirements do you need to become a data analyst in the UK?

No specific qualifications are legally required to work as a data analyst in the UK. What matters most to hiring managers at entry level is demonstrable applied skill: can you write SQL, clean a messy dataset, build a chart that tells a story? A degree in a quantitative subject can accelerate your path and open doors in some sectors (particularly financial services and consultancy), but it's not a prerequisite. The Level 4 Data Analyst programme under ST0118 is specifically designed for people entering or progressing in data careers without requiring a prior degree.

How much do you earn during a Level 4 Data Analyst apprenticeship?

During a Level 4 Data Analyst apprenticeship, the apprenticeship minimum wage applies as the legal floor — but most employer-sponsored programmes pay at or above the National Living Wage, and many pay considerably more. The actual salary depends entirely on the employer's own pay framework, not on the training provider. Because you are employed and earning throughout the programme, there is no income gap of the kind that full-time bootcamps can create. If you are negotiating an employer-sponsored place, the salary is set by your employer and is worth clarifying before you enrol.

Is a funded employer programme or a bootcamp better for salary outcomes?

No published study directly compares salaries of bootcamp graduates vs employer-programme completers in equivalent roles, so any precise figure claiming a "X% salary uplift" for one route should be treated with caution. The structural difference is clear: a funded Level 4 employer programme means you earn throughout training and build skills in a real business context; a bootcamp typically involves a period of reduced or no income. Both can lead to the same role and the same salary band. The choice depends less on salary outcome and more on your current employment situation — and whether your employer will sponsor the training. Our apprenticeship vs bootcamp guide covers this in detail.

What roles can a data analyst progress into?

From a data analyst role, common UK career moves include: senior/lead analyst, analytics manager, data engineer (higher technical depth, typically higher pay), BI developer, product analyst, and — with further study — data scientist. The Level 5 Data Engineering programme at iO-Sphere is one structured path for analysts ready to move into engineering. Progression into management or engineering exits the SOC 3544 classification and typically enters better-paid occupational categories, so the ONS median is a floor reference for the career, not a ceiling.

Salary data: ASHE Table 14: Occupation (4-digit SOC 2020), 2025 provisional — Office for National Statistics, published 23 October 2025. Figures are gross annual pay for SOC 3544 (data analysts), UK, 2025 provisional.

Exploring a data analytics career or want to understand how a funded Level 4 programme works? The Advanced Data & AI programme page is the right next step.