Data Intelligence Analyst

A Data Intelligence Analyst pulls together data from different systems, checks it makes sense, and turns it into reports, dashboards and briefings that help an organisation make decisions. The "intelligence" part usually means the work is aimed at a specific audience with a specific question - commercial teams wanting to know which products or customers are profitable, operations teams wanting to know where delays happen, or in public sector and policing contexts, teams wanting to understand patterns of risk, demand or crime. In practice you spend your time extracting data, cleaning it, analysing it and then explaining what you found to people who are not analysts.

Starting salary: £25k–£35k
Live graduate jobs: 2 open now
Main way in: Direct entry to a junior or graduate-level analyst post…
They usually ask for: A degree is usually expected but the subject matters less than…

Approximate graduate salary

Typically around £25,000–£35,000 to start, though this varies widely. Public sector and smaller regional employers tend to sit at the lower end, London-based financial services, tech and consultancy roles at or above the upper end, and structured graduate schemes often pay more than direct-entry junior analyst posts in the same sector.

What you'd actually do

Writing SQL queries to pull data out of databases or a data warehouse - this is the single most common daily task in most versions of the job
Cleaning and checking data: spotting duplicate records, missing fields, inconsistent date formats or figures that don't reconcile with another system, and deciding how to handle them
Building or updating dashboards and reports in a business intelligence tool such as Power BI, Tableau or Looker, so that other teams can see current numbers without asking you
Answering ad hoc questions from colleagues - 'why did referrals drop last month?', 'which regions are driving the increase?' - which usually means a short piece of analysis plus a written or verbal explanation

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Producing a regular briefing, analytical product or intelligence report on a cycle (weekly, monthly or quarterly), summarising trends and flagging anything that has changed
Sitting in meetings with the teams you support to understand what they actually need, because the question people ask first is often not the question they need answered
Documenting how a metric is defined and where the data came from, so figures stay consistent between reports and teams

How graduates get in

Direct entry to a junior or graduate-level analyst post advertised as Data Analyst, Insight Analyst, Business Intelligence Analyst or Data Intelligence Analyst - this is the most common route and many of these roles are open to any degree subject if you can show the technical basics
Structured graduate schemes in data and analytics, common in banking, insurance, retail, utilities, consultancies and large public bodies; these rotate you around teams and usually fund training
The Civil Service Fast Stream and equivalent public sector analyst routes, and police force or law enforcement analyst entry schemes where 'intelligence analyst' is an established career track with its own training
Moving sideways from an adjacent job - reporting assistant, operations coordinator, customer service or finance administrator - by taking on the reporting work in that team and then applying internally; very common and often underrated

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A data analytics or data science apprenticeship (including degree apprenticeships), or a postgraduate conversion MSc in data science or business analytics if your first degree was non-numerical
Internships, placement years or short data projects - even an unpaid analysis project for a society, charity or small business gives you something concrete to talk about at interview

What employers ask for

A degree is usually expected but the subject matters less than you'd think. Economics, maths, statistics, computer science, geography, psychology and business are all common; humanities graduates do get in if they can demonstrate SQL and Excel competence
Many employers ask for a 2:1, but plenty of analyst roles - particularly in the public sector, smaller firms and operational teams - ask for a 2:2 or do not specify, and weight a practical test more heavily
Demonstrable SQL and Excel are the most frequently requested hard requirements. Python or R is often listed as desirable rather than essential, and whether it's genuinely used varies enormously by employer
Experience with at least one BI/dashboarding tool (Power BI and Tableau are the most commonly named in UK adverts) is frequently asked for, though some employers will train you

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For police, defence or government intelligence analyst roles you will need UK security clearance, which means residency requirements and a vetting process - this rules some candidates out and takes time
No single mandatory professional qualification exists. Some employers value vendor certificates (Microsoft data certifications, for example) or, in public sector analysis, internal training such as intelligence analysis courses

Skills that matter

SQL

Almost every question you are asked starts with getting the right rows out of a database, and you will write queries most days.

Data cleaning and validation judgement

Real organisational data is messy, and knowing when a figure looks wrong - and chasing it down rather than publishing it - is what separates a trusted analyst from an ignored one.

Explaining findings to non-technical people

Your output is only useful if a manager with no statistics background can act on it, so you spend real time choosing the right chart, writing a clear summary line and cutting detail.

Framing the question

Requests arrive vague or over-specified, and the skill is turning 'can I have the sales data' into a defined question with a defined time period and a defined comparison.

Dashboard and visualisation design

Badly built dashboards get abandoned, so understanding what to show, what to filter and how to make numbers reconcile is a large part of the job's visible output.

Statistical literacy (not necessarily advanced maths)

You need to know when a change is just normal variation, how seasonality distorts comparisons and why correlation in a dashboard isn't evidence of cause.

Care with sensitive data

You will often handle personal or confidential information, so understanding data protection basics and access controls is part of doing the role properly rather than an afterthought.

Putting these on a CV? We counted which skills 12,914 live graduate adverts ask for, and what to do with the answer — part of our application advice.

Where it leads

Junior or graduate analyst: you mostly answer defined requests and maintain existing reports while learning the organisation's data and systems. Typically the first year or two, though this varies.
Analyst / Senior Analyst: you own a reporting area or a stakeholder group, scope your own pieces of work, and start being asked for recommendations rather than just numbers. Timelines vary a lot - faster in small organisations where you are the only analyst.
A branching point. Common directions are: data science and machine learning (usually requires building stronger Python and statistics); analytics engineering or data engineering (building the pipelines rather than using them); or deeper domain specialism such as pricing, risk, fraud or crime analysis.
Lead Analyst, Analytics Manager or Head of Insight: running a small team, setting standards for how metrics are defined, and managing demand from the business rather than doing all the analysis yourself.
Longer term, routes include Head of Data / Data Director in larger organisations, analytics consultancy, or moving into the commercial or operational side you've been supporting - analysts often have an unusually good map of how the whole organisation works.

What people get wrong

“The job is mostly building machine learning models.”

In most UK analyst roles the modelling component is small or absent. The bulk is SQL, data cleaning, reporting and conversations with stakeholders. Modelling-heavy work tends to sit in data scientist roles, which are usually a separate and more senior hire.

“'Intelligence' means spying or national security.”

In commercial settings it usually just means business intelligence - structured reporting and insight. It does mean something closer to the traditional sense in policing, defence and some government roles, where the work involves analysing intelligence reports and feeding tasking decisions, and where vetting is required. Check the advert's sector before assuming either.

“You need a maths or computer science degree.”

Many employers care far more about whether you can write a working SQL query and explain a chart than what your degree says. Non-numerical graduates routinely get in via self-taught skills, a portfolio project, or an internal move from another team.

“The technical skill is the hard part.”

Most analysts find the technical side becomes routine within a year. The persistently difficult part is stakeholder work - getting people to tell you what they actually need, pushing back on a request that would produce a misleading answer, and getting anyone to act on findings they didn't want to hear.

Where this varies

This title covers genuinely different jobs depending on sector. In retail, financial services, utilities and tech it is effectively a business intelligence or commercial insight role: dashboards, KPIs, customer and product analysis. In policing, defence, border and some government bodies it is an intelligence analyst role in the traditional sense - assessing information from multiple sources, producing problem profiles and briefings, and supporting operational decisions, with security vetting attached. There is also a fraud and financial crime version, found in banks and insurers, that blends both. Team size matters too: in a large organisation you may specialise narrowly and have engineers supplying clean data, while in a small one you will do everything from extracting the data to presenting to the board. Tooling varies accordingly - some employers are entirely Excel and Power BI, others expect Python, dbt and a modern cloud warehouse.

See all 2 live Data Intelligence Analyst jobsFrom employers' own careers sites, updated daily Tailor your CV for this roleFree with an account, 3 a month

General guidance about the role across the UK market, not about any specific employer. Entry routes and requirements vary — always check the individual job advert.