Customer Data Architect

SuccessFactors
Greater London
6 months ago
Applications closed

Related Jobs

View all jobs

Principal Data Architect

SC Cleared Data Architect

Data Architect

SC Cleared Data Architect

Data Architect - Halifax; Home Based

Data Architect

Customer Data Architect

Customer Data Architect

Waterloo - Hybrid Working
Full Time
Permanent 
Grade 4

 

At Currys we’re united by one passion: to help everyone enjoy amazing technology. As the UK’s best-known retailer of tech, we’re proud of the service our customers receive – and it’s all down to our team of 25,000 caring and committed colleagues. Working as one team, we learn and grow together, celebrating the big and small moments that make every day amazing.

 

The Role of the Customer Data Architect is  design and implement customer data architecture that enable personalised experiences while ensuring privacy, quality, and accessibility of customer information across all touchpoints.

 

Role overview:

 

 

As part of this role, you'll be responsible for:

 

•    Design customer data models that support omnichannel personalisation and analytics
•    Architect identity resolution and customer 360 solutions across multiple data sources
•    Implement data quality frameworks specific to customer data domains
•    Design consent management and preference architectures that comply with regulations
•    Create customer segmentation frameworks that support marketing and analytics use cases
•    Partner with MarTech teams to ensure optimal data flow to activation platforms
•    Document customer data lineage and maintain data dictionaries
•    Support customer data platform (CDP) implementation and integration projects

 

You’ll work closely with the AI & Monetisation team, partnering with engineering colleagues, MarTech specialists and data scientists to design and deliver customer data solutions. You’ll collaborate with marketing and commercial teams to ensure data flows seamlessly into activation platforms, supporting personalised experiences. You’ll also engage with compliance and governance stakeholders to make sure privacy, and regulatory standards are always met.

 

 

You will need:

 

•    Deep expertise in customer data management and architecture
•    Experience with customer data platforms (CDPs) and identity resolution
•    Strong understanding of marketing technology ecosystems
•    Knowledge of real-time data processing for personalisation
•    Proficiency in SQL and data modelling techniques
•    Understanding of privacy regulations affecting customer data
•    Experience with event-driven architectures
•    Background in retail or e-commerce customer data is desirable
•    Degree in Computer Science, Information Systems or related field, or equivalent professional experience
•    CDP or MarTech certifications are beneficial
•    Privacy certifications are a plus

 

 

We know our people are the secret to our success. That's why we're always looking for ways to reward great work. You'll find a host of benefits designed to work for you, including:

 

  • Company Pension
  • Company Bonus
  • Private Medical

 

Why join us:

 

Join our team and we'll be with you every step of the way, helping you develop the career you want with new opportunities, on-going training and skills for life.

 

Not only can you shape your own future, but you can help take charge of ours too. As the biggest recycler and repairer of tech in the UK, we’re in a position to make a real impact on people and the planet. 

 

Every voice has a space at our table and we're committed to making inclusion and diversity part of everything we do, including how we strengthen our workforce. We want to make sure you have a fair opportunity to show us your talents during our application process, so if you need any additional assistance with your application please email and we'll do our best to help.

 

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 Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

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

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

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

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.