Data Architect

London
22 hours ago
Applications closed

Related Jobs

View all jobs

Data Architect

Data Architect

Data Architect

Data Architect

Data Architect

Data Architect

Data Architect

3 days a week onsite in London

35hr working week with flexible working hours

We're looking for an experienced Data Architect to join a well-established company who are going through an enterprise-wide modernisation programme. This is a brand-new role within the business and you'll be responsible for defining and evolving the data architecture that underpins enterprise-scale BI and self-service analytics across a large, complex organisation operating across the UK and Europe.

This is a strategic and hands-on role where you will set the technical vision, standards, and frameworks for modern data platforms, ensuring they are scalable, secure, cost-effective, and aligned with business priorities. You will act as a technical authority for data architecture, working closely with BI Engineers, Developers, Product, and senior stakeholders to enable high-quality analytics and data products today and in the future.

What you'll be doing

Architecture & Strategy

Assess existing data architectures, documenting current-state models, pipelines, tools, and standards
Define and maintain the enterprise data architecture vision and roadmap aligned to BI strategy and business goals
Design logical and physical data models optimised for reporting, analytics, and self-service BI
Establish and govern architectural patterns (e.g. medallion architecture, dimensional modelling, data vault)
Design cloud-based data platform architectures (AWS preferred), including data storage, processing, and consumption layersTechnology Leadership

Evaluate and recommend modern data technologies and tooling
Stay current with industry trends such as open table formats (Apache Iceberg, Delta Lake), data observability, and cloud-native services
Lead proofs-of-concept and technical assessments for new technologies
Ensure the data architecture remains modern, performant, and future-proofData Modelling & Governance

Define standard business entities, metrics, and KPIs for consistent reporting
Review and approve complex data models created by BI Engineers
Design and embed data governance frameworks covering ownership, quality, security, and complianceCollaboration & Influence

Partner with BI leadership to shape data and analytics strategy
Provide architectural guidance and mentorship to BI Engineers and Developers
Work closely with frontend BI Developers to ensure data structures support performant dashboards
Translate business requirements into clear, practical architectural solutions
Facilitate architecture workshops and discussions with technical and non-technical stakeholdersWhat we're looking for

Essential experience

Extensive experience in data architecture, designing and delivering enterprise-scale data solutions
Strong expertise in data modelling with excellent SQL skills
Deep knowledge of modern data engineering patterns (ETL/ELT, data lakes, lakehouse, warehousing)
Hands-on experience with cloud data platforms (AWS preferred: Redshift, Athena, S3, Glue; Azure or GCP beneficial)
Experience with data governance, data quality, metadata management, and regulatory considerationsPersonal attributes

Strong business acumen and ability to link data architecture to real business outcomes
Pragmatic mindset: balancing architectural best practice with delivery and cost constraints
Curious, continuous learner with an interest in emerging technologies
Confident communicator who can influence and build trust across technical and business teamsThis is a great opportunity where you'll get the opportunity to shape the data architecture for a large, multi-country organisation and work with modern cloud and analytics technologies at scale. You'll play a strategic role with real influence over how data enables the business and will collaborate with experienced BI and data professionals in a growing, evolving environment.

If you're passionate about building robust, scalable data architectures and want to have a meaningful impact on how data is used across an organisation, please send your CV

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.