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Legl

Analytics Engineer

London
Posted 8 days ago
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Hi 👋 We’re Legl.

Legl is building the operating system for modern legal services.

We help law firms and regulated businesses replace manual, fragmented workflows with intelligent software from client onboarding and compliance to payments, risk, and reporting.

Legal work is high-stake - it’s regulated, complex, and deeply impactful - and our mission is to help regulated firms grow faster, run their businesses more profitably, manage risk intelligently, and deliver great client experiences.

We’re backed by leading European VCs, scaling quickly, partnered with over 600 law firms including 50 of the UK’s top 200, launched in the UK and Australia - and entering our next phase of growth.

We Work Best When

  • AI is the central-operating model: not a tool or a future plan - but the way we run.
  • Decisions live with people: you're trusted to make calls and own them.
  • Think deeply, execute quickly: speed and rigour, not speed or rigour.

What You’ll Do

Our analytics stack is Snowflake for the warehouse, dbt Core for transformation, Fivetran for ingestion, GitHub Actions for CI and scheduling, Metabase for BI, and a Snowflake Cortex semantic layer that lets colleagues and AI tools query the business in plain English. We work in Claude Code day to day, alongside the usual editor and terminal.

The analytics stack supports the whole business, so you would be working with Finance, Sales, Customer Success and Product rather than for any one of them. The goal is that those teams can answer their own questions and make decisions from data without waiting on us. What you would genuinely own is a domain, end to end: its models, its tests, its documentation, and the definitions behind its numbers. The analytics layer and the semantic layer are shared across the team, and you would contribute to both.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

Start with a chat, not a search bar

Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

The domain we would want you in first is product analytics: how new customers activate, how features get adopted, and how usage develops over the life of an account. These are the questions the business asks most often and the ones our models currently answer least well, so there is a lot of room to shape how we measure them rather than inheriting someone else's definitions.

As a Data Engineer At Legl, You'll

  • Model the warehouse. Design and maintain dbt models, sources, tests and documentation across our layered architecture, and keep naming and structure coherent as it grows.
  • Work with Product as features ship. Get involved early enough to know what a new feature will emit, so it lands in the models correctly the first time rather than being retrofitted once someone notices a number looks wrong.
  • Define metrics, and contribute to the semantic layer. Get definitions agreed and codified so a KPI means the same thing in a board pack, a dashboard and an AI answer.
  • Build for self-serve. Design models that people can actually use themselves, whether they reach them through a semantic layer or a BI tool, and retire what nobody uses.
  • Data quality and observability. Extend our test suite, tune alerting so failures mean something, and keep the nightly pipeline honest.
  • Consolidate rather than accumulate. Extend and reshape what exists before adding to it, and retire what is no longer load-bearing. A smaller, clearer estate is where we want to get to, and this is a role that helps take us there.
  • Governance and privacy. We model how law firms use Legl. We do not model the personal data of the clients those firms serve, which stays inside the product and out of the warehouse. Keeping that boundary intact is a live decision every time we bring in a new source.

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This Role Is a Great Fit If You…

  • Are an analytics engineer, BI engineer, or modelling-heavy analyst with strong SQL and data modelling fundamentals, including dimensional design, slowly changing dimensions and incremental patterns.
  • Have hands-on dbt experience in a cloud warehouse, and are comfortable reviewing SQL in pull requests.
  • Use AI tooling as a normal part of the job. We work in Claude Code daily, for modelling, review and investigation, and you would too. Just as important is knowing how to make that safe: somewhere a bad change is cheap, and enough verification to know a change is right before it goes near production. Speed of generation is only useful if the checking keeps up.
  • Reconcile new logic against what it replaces and quantify the difference before calling it done.
  • Communicate clearly with non-technical partners and enjoy turning a vague question into something measurable.

This Role Is Not a Great Fit If You…

  • You wait to be handed fully specified requirements, and see the job as fulfilling requests rather than solving problems.
  • Are a data scientist or ML engineer. This role is modelling, quality, semantics and BI.
  • Are a people manager. This is an IC role with wide influence.
  • You treat AI as either magic or a threat, and haven't actually shipped LLM-enabled work.

Legl is a fast-growing, B2B SaaS platform with a mission to bring the legal industry into the 21st century. We’re making legal services simpler for everyone by changing the way that firms take on new clients, making it easy to pay for legal services, and ensuring that everyone can seamlessly access the law.

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Skills

SQL
Data Modelling
dbt
Snowflake
Dimensional Design
Slowly Changing Dimensions
Incremental Patterns
Product Analytics
BI Tooling
GitHub Actions
Fivetran
Metabase
AI Tooling
Claude Code
Data Quality
Data Governance

Location

London, England, United Kingdom

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