Analyst Engineer

An analyst engineer sits between the people who ask business questions and the systems that hold the data or run the technical process. In most cases the job means taking messy raw data, cleaning and modelling it into something reliable, and building the reports, dashboards or small pieces of software that other teams use to make decisions. The title is used in two fairly different ways in the UK - in data and software teams (sometimes called "analytics engineer"), and in engineering and manufacturing firms, where it means someone who analyses the performance of physical systems, tests or designs.

Starting salary: £28k–£38k
Live graduate jobs: 3 open now
Main way in: Direct application to a junior or graduate analyst engineer /…
They usually ask for: A degree is usually expected

Approximate graduate salary

Typically around £28,000–£38,000 to start, though this varies widely - London and large tech or financial employers sit at or above the top of that range, while smaller firms, charities, public sector and roles outside the big cities often start lower.

What you'd actually do

Writing SQL queries against a company's data warehouse (the central store of business data) to pull out figures for a specific question - for example, why a particular product line's numbers dropped last month
Building and maintaining data 'models' - reusable, tested sets of transformations that turn raw system data into clean tables everyone trusts - often using a transformation tool and version control such as Git
Building or updating dashboards and reports in a business intelligence tool so that finance, operations or marketing colleagues can self-serve rather than asking you every week
Sitting with a non-technical stakeholder to work out what they actually need, which is frequently different from what they asked for, and agreeing definitions (what exactly counts as an 'active customer'?)

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Investigating things that have broken - a nightly data load that failed, a number that disagrees between two reports - and tracing it back through the pipeline to the source
Writing documentation and tests so that the figures you produce can be checked and reused, and reviewing colleagues' code
In engineering and manufacturing settings instead: analysing test rig or sensor data, running calculations or simulations against design requirements, and writing up findings in technical reports for design teams

How graduates get in

Direct application to a junior or graduate analyst engineer / analytics engineer post. This is probably the most common route, especially at mid-sized tech, retail, media and consultancy firms that hire in ones and twos rather than running big schemes.
A structured graduate scheme in data, technology or engineering at a large employer - banks, insurers, utilities, telecoms, retailers, the Civil Service and defence contractors all run these. You may rotate through analysis, engineering and reporting teams before specialising.
Moving across internally from a data analyst, business analyst, reporting or operations role once you have picked up SQL and some coding. Very common - plenty of analytics engineers never applied for the title directly.
A placement year or summer internship in a data or engineering team, converted into a graduate offer. Strong route where it exists.

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Apprenticeship or school-leaver routes (data analyst and engineering apprenticeships at Level 4 and above) followed by progression. Less common for graduates but a real path into the same job.
Conversion routes for non-technical graduates - a data science or software MSc, or a reputable bootcamp plus a portfolio of projects. Bootcamps work for some employers and are ignored by others, so treat them as a supplement to demonstrable project work rather than a guarantee.

What employers ask for

A degree is usually expected, and for the data-side version the subject matters less than the evidence you can code. Maths, statistics, economics, computer science, physics and engineering are the most common, but geography, psychology and business graduates get in regularly if they can show SQL and analysis work.
For the engineering-industry version of the title, a relevant engineering, physics or materials degree is normally a hard requirement, and employers may expect it to be accredited by a professional institution if you want chartership later.
Grades: many employers ask for a 2:1, some accept a 2:2 with relevant experience, and a growing number run CV-blind or skills-test-first processes where the classification matters less. This varies a lot.
Practical evidence of SQL, and usually Python or R. For analytics engineering specifically, familiarity with version control (Git), a transformation framework such as dbt, and a BI tool (Power BI, Tableau, Looker) is increasingly expected - though many employers will train you on their specific stack.

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Most roles involve a technical assessment: a take-home data exercise, a live SQL test, or a case study where you present findings to a panel. Preparing for these matters more than polishing a cover letter.
Professional qualifications are not usually required to start. In engineering firms, working towards IEng or CEng status through an institution is common; in data roles, vendor certifications (cloud platforms, BI tools) are optional extras rather than entry tickets.

Skills that matter

SQL, to a genuinely fluent level

It is the day-to-day language of the job - joins, window functions and aggregations are how you answer almost every question you'll be asked.

Data modelling

Deciding how tables should be structured so the same number means the same thing everywhere is the core craft that separates an analyst engineer from someone who just writes queries.

Software engineering habits

Version control, code review, testing and writing readable code are what make your work maintainable rather than a spreadsheet nobody else can run.

Translating vague business questions into precise definitions

Stakeholders ask 'how are we doing?' and your job is to turn that into a specific, measurable, agreed question before you write any code.

Debugging and stubbornness

A large slice of the week is tracing why a number is wrong through several systems, and the people who are good at this simply refuse to accept an unexplained discrepancy.

Explaining technical findings to non-technical people

Your output is only useful if a marketing manager or plant supervisor trusts it and acts on it, which means clear charts and plain-English caveats about what the data can't tell them.

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

Graduate or junior analyst engineer: working on well-defined tickets, building reports and models under review, learning the company's data and systems. Typically the first year or two, though this varies by employer.
Analyst engineer / analytics engineer: owning a domain (say, finance or supply chain data) end to end, being the person stakeholders come to directly, and reviewing others' work.
Senior: designing how data is structured across several teams, setting standards, mentoring juniors, and being involved in which tools the company buys. Time to reach this varies widely - a few years at a fast-growing company, longer in large structured organisations.
From senior, the paths fork. Towards data engineering (building the pipelines and infrastructure), towards analytics or data science leadership, towards analytics manager or head of data, or sideways into product management or consultancy where the mix of technical and commercial skills is valued.
In engineering-sector versions of the role, progression often runs towards chartered engineer status and then senior design, technical specialist or engineering management positions.

What people get wrong

“It's a maths-heavy job full of statistics and machine learning.”

For most analyst engineers the hard parts are data plumbing, definitions and stakeholder management. Advanced statistics come up far less often than careful SQL and arguing about what 'revenue' means.

“'Analyst' means you only look at data, and 'engineer' is just decoration.”

The engineering half is real - you're writing code that runs on a schedule, lives in version control and gets reviewed, and if it breaks at 3am someone notices. It is much closer to software development than to spreadsheet analysis.

“You need a computer science degree.”

On the data side, many people arrive from economics, physics, geography or social sciences, or move across from an operations or reporting job. Demonstrable SQL and project work usually counts for more than the subject on the certificate - though the engineering-industry version of the title is genuinely stricter about degree discipline.

“The title means the same thing everywhere.”

It doesn't. At a software or retail company it means analytics engineering with data warehouses; at a defence, automotive or energy firm it can mean analysing test and simulation data on physical systems. Read the advert's responsibilities carefully rather than trusting the title.

Where this varies

The biggest variation is what the title actually means. In tech, retail, media and consultancy it is essentially analytics engineering: SQL, data warehouses, dbt-style transformation and BI dashboards. In aerospace, automotive, defence, energy and manufacturing, an analyst engineer is more likely to be analysing physical test, sensor or simulation data against engineering requirements, and the entry requirements and progression (towards chartered status) look quite different. Size matters too: at a small company you may be the only data person and will do everything from pipelines to presenting to the board, while at a large one you'll sit in a specialised team with platform engineers, data scientists and BI developers alongside you. Hybrid working is common in the data version of the role; the engineering version is more often site-based because of lab, rig or plant access.

See all 3 live Analyst Engineer 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.