UK

United Kingdom · International business · Lead (8-12 years)

Lead BI Developer / BI Architect

Here is the whole job, in plain words. What it is, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

Start my Lead BI Developer / BI Architect plan, free

Free to start: a plan built for this role, and a Future Fluency module to try first. No card.

Keep this job description

Where should we send it?

One email: what AI is changing in this job, and where to start free. With a link back here. Nothing else follows unless you confirm your address.

Upskilling a team in this role? Talk to us

  • Experience bandLead (8-12 years)
  • Direct reports3-5 reports
  • Reports toBI Manager (Region)
  • UK framework levelUsually a manager, or the deepest specialist in a team

Also advertised as Principal BI Engineer · Senior Data Warehouse Architect · Regional BI Solutions Lead

Built on 43,079 real UK job descriptions we analysed · grounded in qualifications employers recognise

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 5 of 10 standards
NCC Education Level 5 Extended Diploma in Computing with Data Science NCC Education Limited · Level 5 · covers 3 of 10 standards
Pearson BTEC Level 5 Higher National Diploma in Digital Technologies Pearson Education Ltd · Level 5 · covers 3 of 10 standards
Qualifi Level 5 Diploma in AI Qualifi Ltd · Level 5 · covers 2 of 10 standards
Pearson BTEC Level 5 Higher National Diploma in Cloud Computing Pearson Education Ltd · Level 5 · covers 2 of 10 standards
Pearson BTEC Level 5 Higher National Diploma in Business Pearson Education Ltd · Level 5 · covers 1 of 10 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Data Analytics Pearson BTEC Level 5 Higher National Diploma in Computing for England
Introduction to Data Science and Big Data NCC Education Level 5 Extended Diploma in Computing with Data Science
Visualisation Qualifi Level 5 Diploma in AI
Business Intelligence Pearson BTEC Level 5 Higher National Diploma in Cloud Computing

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
AI Governance Fluency using AI responsibly
Automation Fluency building AI into how work runs
Frontier Fluency the next wave, beyond mainstream AI
Start my Lead BI Developer / BI Architect plan, free
Your Plan Illustration

Built for Lead BI Developer / BI Architect

4 units that map to this job, from the qualifications that cover it.

  1. Data Analytics Pearson Education Ltd · covers 5 of 10 standards Level 5
  2. Introduction to Data Science and Big Data NCC Education Limited · covers 3 of 10 standards Level 5
  3. Visualisation Qualifi Ltd · covers 2 of 10 standards Level 5
  4. Business Intelligence Pearson Education Ltd · covers 2 of 10 standards Level 5
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Lead BI Developer / BI Architect?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skills this role is being asked for

  • Prompt Engineering & LLM Integration for BI
  • Data Mesh Principles & Decentralised Data Ownership
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Lead BI Developer / BI Architect plan as you set up, starting with a Future Fluency module on using AI in your job. No card.

Your first Future Fluency module is free. After that, your AI tutor is £70 a month.

Start my Lead BI Developer / BI Architect plan, free Ready to pay? Subscribe for £70 a month

3What this role really is

A lead BI developer designs how regional business data is structured, stored and modelled. This role sets how data flows and makes sure it can be trusted.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

Power BI / Tableau (Enterprise Deployment) Expert

Architecting complex, performant dashboards and reports, optimising data models within the tools, managing enterprise features like row-level security, and training business users on advanced capabilities. You'll be the regional expert.

Snowflake (Data Warehouse) Expert

Designing schemas, optimising query performance, managing roles/access control, understanding cost implications, and architecting data sharing solutions. You'll be the primary architect for our regional data in Snowflake.

dbt (Data Build Tool) Expert

Designing, building, and maintaining modular, testable, and version-controlled data transformation pipelines. You'll set the standards for how we transform data in Snowflake.

Talend (ETL/ELT Platform) Advanced

Designing and implementing complex data integration jobs, connecting to various source systems, and orchestrating data flows into our data warehouse. You'll ensure data gets where it needs to go reliably.

Python (pandas, NumPy) Advanced

Writing reusable scripts for complex data analysis, automating reporting tasks that are difficult in SQL, and building custom data validation routines. You won't be a full-time coder, but you'll use it for advanced data manipulation.

Confluence / Jira Advanced

Creating and managing the team's architectural documentation and knowledge base, designing project workflows, sprint plans, and tracking the progress of complex BI initiatives.

Excel (VBA, Advanced Modelling) Advanced

Building complex financial models that connect to data sources, performing ad-hoc analysis, and helping Finance Business Partners integrate BI data into their planning processes. Yes, Excel is still a thing.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
Data Model Design & Architecture Follows existing design patterns, seeks approval for any deviation. Proposes design changes for specific projects, gets sign-off from senior team. Designs complex data models for new domains, consults Lead/Architect on major structural decisions.
Tool/Technology Selection (within BI stack) Uses existing approved tools. Researches and recommends new features within existing tools. Evaluates new tools for specific project needs, makes recommendations to Lead/Manager.
Project Prioritisation (within team) Works on tasks assigned by supervisor. Prioritises own tasks based on project plan, escalates conflicts. Manages priorities for their own workstream, negotiates with stakeholders on delivery dates.
Data Quality Standards Reports data quality issues. Implements data quality checks within their own pipelines. Designs and implements data quality monitoring for a specific domain.

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Dashboard Adoption Rate
Percentage of target business users actively using key dashboards you've designed or overseen.
Target · Over 60% monthly active users on critical regional dashboards.

If 100 regional sales managers are meant to use the Sales Performance dashboard, we'd expect at least 60 to log in and interact with it each month. If it's lower, we need to understand why.

Reduction in Ad-hoc Requests
Decrease in the volume of routine, simple data pull requests coming into the BI team, thanks to your self-service solutions.
Target · A 25% decrease in ad-hoc tickets (categorised as 'simple data pull') year-over-year.

If we get 20 'simple data pull' tickets a week now, we'd aim for that to drop to 15 within a year because users can find the info themselves through your self-service tools.

Data Pipeline Reliability (SLA Adherence)
The percentage of time your critical data pipelines (ETL/ELT processes) deliver fresh, accurate data within defined service level agreements.
Target · 99.5% uptime and data freshness within 2 hours of source system updates.

If the regional sales dashboard is meant to update by 9 AM every day, and it's late more than twice a month, that's a problem. We're looking for consistent, reliable delivery.

Query Performance Optimisation
The average execution time for critical queries powering regional dashboards and reports.
Target · Average query execution time for top 10 most used dashboards under 10 seconds, with no single query exceeding 30 seconds.

If a key dashboard takes 45 seconds to load, users won't wait. You'll be expected to diagnose and fix those bottlenecks, aiming for snappy, instant data access.

Technical Design Quality
The elegance, scalability, and maintainability of the data models and BI solutions you architect.
  • Positive feedback during peer code reviews
  • new features can be added easily without breaking existing ones
  • clear, consistent documentation
  • minimal technical debt accrual
  • solutions stand the test of time and scale with business growth.
Stakeholder Trust & Influence
How much regional business leaders and data engineering peers rely on your technical judgment and proactively seek your input on data strategy.
  • You're invited early to discussions about new business initiatives that require data
  • your recommendations on data architecture or tool selection are typically adopted
  • business VPs trust your 'sanity check' on their numbers
  • you're seen as the authority for BI technical direction in the region.
Mentorship Effectiveness
The growth and development of the junior and mid-level BI developers/analysts you guide.
  • Your mentees show clear improvement in their technical skills and problem-solving abilities
  • they're able to take on more complex tasks independently
  • they feel supported and regularly seek your advice
  • positive feedback in 1-to-1s and performance reviews about your guidance.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Building Robust, Scalable Systems

You get a real kick out of designing elegant data models and pipelines that just *work* and can handle growing data volumes. You're always thinking about the long-term maintainability and performance of your solutions.

Spending an afternoon refactoring a complex dbt model to be more modular and performant, knowing it will save countless hours of debugging down the line, feels like a win.

Solving Complex Data Puzzles

You love diving deep into messy data, figuring out how to join disparate sources, and untangling complex business logic to create a clean, reliable dataset. The harder the problem, the more engaged you are.

Successfully reconciling sales numbers across three different regional systems, despite inconsistent IDs and date formats, and finally getting a 'single source of truth' for the regional sales team.

Enabling Business Decisions Through Architecture

You're motivated by seeing your data architecture directly enable better, faster business decisions. You're not just building for building's sake; you want to see your work make a tangible impact on the business's success.

Hearing a regional marketing director say that a new dashboard, built on your data model, helped them reallocate £100K of budget to a more effective campaign.

What frustrates people
  • The 'Report Factory' Trap: Constantly being buried in ad-hoc requests for minor dashboard tweaks, preventing you and your team from doing deep, strategic architectural work.
  • Data Quality Firefighting: Spending 50% of your team's time cleaning, validating, and reconciling messy data from legacy source systems instead of building new, valuable solutions.
  • The Battle of Dueling Dashboards: Walking into a meeting where the Sales VP has one set of numbers from Salesforce and the Finance VP has another from the ERP, and you have to be the referee, explaining why your single source of truth is the correct one.
  • Explaining 'Why It's Not Simple': The soul-crushing task of explaining to a senior executive why their 'simple, one-hour request' actually requires 40 hours of data engineering to join three disparate systems and build a robust data model.
  • Regional Politics & Data Hoarding: Navigating country managers who are reluctant to share 'their' data or who challenge any analysis that makes their region look bad, making it hard to build a unified view.
  • The ROI Justification Loop: The constant struggle to secure budget for foundational infrastructure projects (like data governance or a new ETL tool) that don't have a direct, easily quantifiable ROI in the short term.
What this role does not give you
  • A perfectly clean, well-organised data environment from day one. You'll inherit some legacy challenges.
  • A purely hands-off, strategic role. You'll still be getting your hands dirty with code and architecture.
  • A quiet, predictable work schedule. There will be urgent requests and unexpected data issues.

8Who you work with

You'll directly influence the quality and speed of decision-making for our entire international business region. Your designs will underpin critical reporting for sales performance, marketing effectiveness, and operational efficiency. Get it right, and we're agile and informed. Get it wrong, and we're flying blind, relying on gut feelings instead of solid data.

Inside the business
  • BI Manager (Region)
  • Regional Sales VPs
  • Regional Marketing Directors
  • Head of Data Engineering
  • Finance Business Partners
  • Product Leads
Outside the business
  • Data platform vendors (e.g., Snowflake, Power BI)
  • External consultants for specific projects
  • Industry peers for best practice sharing

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • Proven experience (at least 3-5 years) as a Senior BI Analyst or Data Engineer, with a track record of leading technical projects and designing data solutions.
  • Demonstrable expertise in SQL, data warehousing concepts, and at least one major BI visualisation tool (Power BI or Tableau).
  • Experience mentoring junior team members and providing technical guidance.
  • A solid understanding of the full data lifecycle, from ingestion to reporting.
  • Experience working in a complex, multi-stakeholder environment, ideally within an international business context.

10What to practise next

Where the job is going, and what to do about it starting this week.

Real-time Analytics Architectures

Our business is increasingly demanding real-time insights, not just daily or weekly reports. You'll need to understand how to design and implement architectures that can process and analyse data with minimal latency.

Stream Processing (Kafka, Flink) · Low-Latency Data Stores · Event-Driven Architectures · Lambda/Kappa Architectures

  • This week: Research the basics of Kafka and its role in data streaming.
  • This month: Identify a regional business process that would significantly benefit from real-time analytics; outline the data sources and potential impact.
  • Month 2: Work with Data Engineering to explore a small proof-of-concept for a real-time data pipeline, perhaps for website clickstream data.
  • Month 3: Present a high-level architectural proposal for a real-time analytics solution to your BI Manager.

Quick win: Start looking at our existing data sources: which ones could potentially provide real-time data? What business questions could be answered immediately, rather than waiting for tomorrow?

Advanced Data Security & Privacy Engineering

With increasing data volumes and stricter global regulations (GDPR, LGPD, etc.), simply 'knowing' about privacy isn't enough. You'll need to engineer privacy and security directly into your data architectures.

Data Masking & Anonymisation Techniques · Homomorphic Encryption (conceptual) · Zero-Trust Data Access · Data Residency & Sovereignty

  • This week: Review our current data security policies and identify potential gaps in our BI architecture.
  • This month: Take an online course on data privacy engineering or advanced data security in cloud environments (e.g., AWS, Azure, Snowflake).
  • Month 2: Propose an enhancement to our existing data access control framework in Snowflake to better enforce least privilege principles.
  • Month 3: Collaborate with our legal and security teams to understand upcoming regional privacy regulations and their architectural implications.

Quick win: Audit one of your existing data models for sensitive data. Could you implement row-level security or data masking more effectively today?

11Staying current once you are in

What people here do to keep up
  • Regularly attend industry conferences (e.g., Data + AI Summit, Snowflake Summit, Power BI World Tour) to stay abreast of new technologies and best practices.
  • Actively participate in online data communities (e.g., dbt Slack, Data Engineering Weekly newsletter) to learn from peers and contribute your own insights.
  • Lead internal knowledge-sharing sessions or 'lunch and learns' for the BI team on new architectural patterns or tools.
  • Pursue advanced online courses or specialisations in areas like cloud data architecture, real-time analytics, or data governance from platforms like Coursera, edX, or DataCamp.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Prompt Engineering & LLM Integration for BI

Competitors are already using Large Language Models (LLMs) to draft reports in minutes that used to take hours, or to generate SQL queries from natural language. Analysts who figure this out will outproduce peers significantly. You'll need to know how to architect these solutions safely and effectively.

  • Context Windows & Token Limits
  • Retrieval Augmented Generation (RAG)
  • Output Validation & Hallucination Detection
  • Prompt Chaining & Agentic Workflows

Data Mesh Principles & Decentralised Data Ownership

As our international business grows, a centralised data team can become a bottleneck. Data Mesh is about empowering domain teams to own their data as 'products,' making it more scalable and agile. You'll need to understand how to architect for this paradigm.

  • Data as a Product
  • Domain-Oriented Ownership
  • Self-Serve Data Platform
  • Federated Computational Governance

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Dimensional Modelling (Kimball Methodology)
  • Data Governance & Stewardship Implementation
  • Strategic KPI Development & Metric Decomposition
  • Agile BI Development & Project Management
  • Stakeholder Influence Mapping & Management
  • Data Transformation & ETL/ELT Pipeline Design

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    Senior BI Analyst / Developer

    3-5 years as a Senior Analyst/Developer

    Skills to master

    • Deep expertise in a specific BI tool (Power BI/Tableau), advanced SQL, data modelling for specific domains, leading small projects, mentoring junior team members.

    You're ready to move on when

    • Consistently delivers complex, high-quality dashboards and reports with minimal supervision.
    • Proactively identifies and resolves data quality issues.
    • Is the 'go-to' person for technical questions within their domain.
    • Has successfully mentored 1-2 junior team members.
  2. 2

    Data Engineer (with BI focus)

    4-7 years as a Data Engineer

    Skills to master

    • Building and maintaining robust ETL/ELT pipelines, cloud data platform expertise (Snowflake, AWS/Azure), strong programming (Python/Scala), understanding of data warehousing principles.

    You're ready to move on when

    • Has designed and implemented scalable data pipelines for critical business data.
    • Understands the needs of BI consumers and can translate data engineering work into analytical value.
    • Is proficient in optimising data for query performance.
    • Shows an interest in the 'last mile' of data delivery to business users.
  3. 3

    Data Architect (from a different domain)

    3-6 years as a Data Architect in another sector

    Skills to master

    • Enterprise data modelling, data governance, cloud architecture, strategic data planning, cross-functional collaboration.

    You're ready to move on when

    • Has successfully designed and overseen the implementation of large-scale data architectures.
    • Can demonstrate strong business acumen and an ability to quickly learn new industry domains.
    • Is skilled at translating business requirements into technical specifications.
    • Has experience influencing senior stakeholders on data strategy.

15Where this role leads

The long view: This work can lead into data engineering leadership, data science leadership, or senior business intelligence roles.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Lead BI Developer / BI Architect is actually changing.

Where it leads

Roles this leads to

The record names a next step, but the catalogue has no page for it yet:

  • BI Manager (Region) (L5)
  • Principal BI Architect (Individual Contributor Path)

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Data Analytics, worked against Lead BI Developer / BI Architect.

Data Analytics Level 5

Applied to your work in Lead BI Developer / BI Architect

The objective of this unit is to enable learners to understand and apply data analytics techniques for decision-making. Learners will be able to apply descriptive, predictive, and prescriptive analytic methods, utilising statistical methods, to convert raw data into actionable insights and determine the best course of action.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

Start my Lead BI Developer / BI Architect plan, free
See Your Progress Grow Illustration
Lead BI Developer / BI Architect
  • Dimensional Modelling (Kimball Methodology)
  • Data Governance & Stewardship Implementation
  • Strategic KPI Development & Metric Decomposition
  • Agile BI Development & Project Management
  • Stakeholder Influence Mapping & Management
  • Data Transformation & ETL/ELT Pipeline Design
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Lead BI Developer / BI Architect is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. BI Manager (Region) (L5)

    3-5 years in the Lead BI Developer / BI Architect role

    This is a step into people management, leading a team of BI developers and analysts. You'll shift from individual technical leadership to broader team leadership and stakeholder management.

    • Vendor Management Managing relationships with BI tool vendors and external partners.
    • Organisational Design Structuring the BI team for optimal efficiency and impact.
    • Cross-Regional Alignment Working with other regional BI Managers to ensure global consistency where needed.

  2. Principal BI Architect (Individual Contributor Path)

    3-5 years in the Lead BI Developer / BI Architect role

    This path deepens your technical specialisation, moving towards setting enterprise-wide architectural standards and solving the most complex, ambiguous data challenges across multiple regions.

    • Multi-Cloud Data Strategy Architecting solutions that leverage multiple cloud providers for data storage and processing.
    • Data Productisation Leading the effort to define and build reusable 'data products' for wider organisational consumption.
    • Advanced Security & Compliance Architecture Designing cutting-edge data security and privacy solutions for global data.
    • Research & Development Piloting and evaluating bleeding-edge data technologies for future adoption.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, you're already swamped. Imagine shaving off a significant chunk of time from your week, not by cutting corners, but by using smart tools. AI isn't here to replace you; it's here to make you a more powerful, more strategic Lead BI Developer.

As an architect, your time is precious. You should be designing, optimising, and mentoring, not getting bogged down in repetitive tasks or manual checks. AI can take on a surprising amount of that grunt work, letting you focus on the big picture and the truly complex problems.

Automated Data Quality Monitoring

Use AI tools like Monte Carlo or Bigeye to automatically scan your data pipelines and warehouses for anomalies, schema changes, and freshness issues. It alerts you before a stakeholder finds an error on a dashboard, saving you from frantic firefighting and protecting your reputation for data integrity.

Accelerated Insight Discovery

Leverage AI-powered 'augmented analytics' features in Power BI or Tableau. These tools can automatically surface key drivers, outliers, and hidden trends in large datasets that even a seasoned human analyst might miss. This speeds up your exploratory data analysis and helps you validate your architectural assumptions much faster.

AI-Powered Technical Documentation & Summaries

After designing a complex data model or building a new pipeline, use a Large Language Model (LLM) to generate a first draft of your technical documentation or an executive summary for your BI Manager. Input your key diagrams and bullet points, and let it create a concise, well-structured narrative. This eliminates the dreaded 'blank page' problem for documentation.

Architecting Natural Language Query (NLQ) Solutions

Beyond just using AI, you'll be instrumental in championing and implementing NLQ tools (like ThoughtSpot or Power BI's Q&A) for our business users. This allows them to ask questions in plain English (e.g., 'what were the top 5 products in Germany last quarter?') and get instant answers, significantly reducing the burden of simple ad-hoc requests on your team and freeing them up for more strategic work.

Common questions

Common questions

How do you become a Lead BI Developer / BI Architect?

Common routes in include Senior BI Analyst / Developer (3-5 years as a Senior Analyst/Developer), Data Engineer (with BI focus) (4-7 years as a Data Engineer) and Data Architect (from a different domain) (3-6 years as a Data Architect in another sector). Times vary with prior experience.

Where can a Lead BI Developer / BI Architect progress to?

This role can lead on to BI Manager (Region) (3-5 years in the Lead BI Developer / BI Architect role) and Principal BI Architect (Individual Contributor Path) (3-5 years in the Lead BI Developer / BI Architect role), depending on the skills you build.

What new skills matter most for a Lead BI Developer / BI Architect?

Increasingly, Prompt Engineering & LLM Integration for BI and Data Mesh Principles & Decentralised Data Ownership. These are the skills our record of this role lists as growing.

Free tools

Want a read on where you stand?

Three free tools, no account needed. Each one ends with a role, a level and a way in.

Read the Zavmo manifesto to understand how you will be taught Meet your tutors

Or try another one

17Where to go from here

Other roles at Level 5

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in international business

Stay in the field you know and move sideways rather than up.
If you leave this industry

The skills involved transfer well. They can lead into broader data engineering leadership, data science leadership, or data-driven product management, in sectors such as FinTech, e-commerce or SaaS as well as international business.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my Lead BI Developer / BI Architect plan, free What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.