Data Architect

Mintel
London
1 year ago
Applications closed

Related Jobs

View all jobs

DataOps Engineer – Data Science Operations

Data Scientist, Machine Learning Engineer, Data Analyst, Data Engineer, AI Engineer, Business Intelligence Analyst, Data Architect, Analytics Engineer, Research Data Scientist, Statistician, Quantitative Analyst, ML Ops Engineer, Applied Scientist, Insigh

Associate Director, Data Science/Gen AI Lead - ER&I

Associate Director, Data Science/Gen AI Lead - ER&I

Associate Director, Data Science/Gen AI Lead - ER&I

Associate Director, Data Science/Gen AI Lead - ER&I

Mintel is searching for an experienced Data Architect to lead the design and implementation of data models and associated standards, while driving a cohesive data architecture vision. In this role, you will collaborate closely with our data teams, who manage extensive data assets and leverage AI and ML technologies. The ideal candidate will take ownership of data architectural processes and work hand-in-hand with Architects, Engineers, Data Scientists, Data Analysts, Product Managers, and other stakeholders to deliver scalable, high-performance data solutions for both customers and internal teams. Additionally, you will play a key role in the continuous enhancement of existing capabilities and migration towards our modern data platform.This hands-on, individual contributor role calls for a strong technical background and substantial experience working in close collaboration with Engineering teams. Success in this position hinges on the ability to work collaboratively, promote teamwork, and build strong partnerships across the organization. The ability to balance trade-offs will be particularly significant, especially as we work with Data Science and Analytics, ensuring practical implementation while maintaining strategic focus.What You’ll DoBecome an expert in Mintel’s data structures, working with technical and non-technical subject matter experts to document existing data assets.Own the creation of data architecture standards that govern the production of data models across Mintel, and the review processes that ensure their proper implementation.Collaborate with Data Architecture to lead glossary development and metadata cataloguing efforts for our data assets.Partner with our data enablement team to define the data structures for reference and master data, working with operational teams to master initial versions of this data.Help to identify and define data management best practices in areas such as data privacy and access control.Collaborate with stakeholders to create conceptual, logical, and physical data models and generate mapping documents that show how data can be transformed between them.Partner with data engineering teams to support the implementation of physical data models and transformation pipelines.Support our data analysis delivery by driving best practice and assisting in the development of models used in the production of visualizations and dashboards.Evaluate and profile existing data systems, helping to identify and troubleshoot any issues that arise in terms of modeling & performance.What We’re Looking ForExcellent communication skills to effectively translate technical concepts into easily understandable business terms.Effective relationship building with senior technical staff so that there is a common understanding of goals and challenges.The ability to adapt, manage and facilitate technological change.A strong background in data modeling and warehouse design.Deep knowledge of SQL, relational and dimensional modeling techniques, and familiarity with data modeling tools like SAP PowerDesigner.Experience in creating and advocating standards for data architecture across delivery teams, with a collaborative mindset to align teams globally.Experience with cloud-native data warehouses (e.g., Snowflake) and BI platforms like Tableau, Sigma or Looker.Knowledge of modern cloud-based technology architectures and designs.Women in TechnologyMintel is committed to building and supporting a diverse workforce, providing opportunities for all. We offer flexible working options, a collaborative and inclusive environment and provide support, development and growth opportunities.#J-18808-Ljbffr

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.

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.

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

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.