Azure Enterprise Data Architect | London | Insurance

London
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Lead Analyst - Data Science_ AI/ML & Gen AI

Portfolio Revenue & Debt Data Scientist

Portfolio Revenue & Debt Data Scientist

Data Scientist

Senior Data Scientist - AI Practice Team

Senior Data Scientist - AI Practice Team

Azure Enterprise Data Architect | London | Insurance 

Lead the Future of Data Architecture

Do you have a deep understanding of modern data infrastructures and cloud-based solutions? Are you an innovative thinker ready to drive large-scale transformation? If your passion lies in utilizing data to enhance decision-making, streamline operations, and ensure regulatory compliance, this opportunity is for you.

About the Organisation

Operating for over a century, this business has evolved into a forward-thinking entity, delivering expertise in financial planning, investments, and risk management. With a customer-centric transformation underway, data and technology are at the heart of its future vision.

Key Responsibilities
Develop and implement a comprehensive data strategy, ensuring alignment with business priorities and technological advancements.
Oversee and maintain enterprise data models, ensuring best practices in management, integration, and security.
Define governance frameworks, data taxonomies, and catalogues to enhance clarity, consistency, and trust in data.
Support AI and machine learning initiatives by structuring high-quality data assets.
Promote data assurance and compliance, ensuring alignment with industry regulations and internal policies.
Collaborate with business leaders, IT architects, and data engineers to establish and maintain world-class data solutions.
Lead innovation efforts, incorporating best practices and industry trends to enhance data capabilities.
Ideal Candidate Profile
Proven expertise in data architecture, cloud platforms (Azure), and governance.
Strong strategic mindset, capable of translating business needs into effective data strategies.
Experience in regulated industries, particularly financial services, is advantageous.
Ability to engage and influence senior stakeholders, working seamlessly across technical and commercial teams.
Deep understanding of data security, integration, and regulatory frameworks.
TOGAF or BCS certification (preferred but not required).

TRANSLATE with x English ArabicHebrewPolish BulgarianHindiPortuguese CatalanHmong DawRomanian Chinese SimplifiedHungarianRussian Chinese TraditionalIndonesianSlovak CzechItalianSlovenian DanishJapaneseSpanish DutchKlingonSwedish EnglishKoreanThai EstonianLatvianTurkish FinnishLithuanianUkrainian FrenchMalayUrdu GermanMalteseVietnamese GreekNorwegianWelsh Haitian CreolePersian TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster Portal Back

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.