Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Architect

Experis
London
3 days ago
Create job alert

Job Description – Data Architect

Role Overview

We are seeking an experienced Data Architect to collaborate with stakeholders and design innovative, scalable, and high-performance data solutions. The role involves shaping enterprise-wide data architectures, developing strategies and governance frameworks, and ensuring solutions align with business objectives and technology strategies. You will play a key role in communicating data findings, building integrations, and delivering real-world value through modern data capabilities.

Key Responsibilities

  • Partner with stakeholders to understand requirements, conduct discoveries, and design data-driven solutions that are scalable, performant, and resilient.
  • Clearly and concisely communicate data architecture, strategies, and findings to both technical and non-technical audiences.
  • Apply data architecture principles to solve complex challenges, including the design and implementation of enterprise-wide data architectures aligned with business and IT strategies.
  • Define and implement data strategies, governance frameworks, and operating models (spanning technology, people, and processes).
  • Design and maintain data models (conceptual, logical, and physical) across databases, data lakes, and warehouses.
  • Enable data integration with diverse systems and platforms via APIs and middleware, covering structured, semi-structured, and unstructured data sources.
  • Contribute to the productionisation of new data capabilities through discovery, prototyping, requirements definition, and implementation.
  • Deliver measurable customer value by ensuring solutions are tailored to business context and operational needs.

Qualifications & Skills

Technical Expertise

  • Proven hands-on experience with data platforms such as Azure, AWS, and Informatica.
  • Strong knowledge of data modelling techniques (e.g., Kimball, Star Schema, Data Vault).
  • Proficiency with cloud-native and DataOps solutions (Azure/AWS stack, event streaming with Azure Event Hubs, Kafka).
  • Experience in Big Data solutions (Hadoop, Cassandra).
  • Understanding of compliance frameworks (e.g., GDPR, ISO 22701) and industry methodologies (e.g., TOGAF, DAMA).
  • Skilled in architecture and design tools (Visio, Draw.io, Archi, SparxEA).

General Skills

  • Eligible for Security Clearance.
  • 5+ years of experience in data-focused roles, including 2+ years in data architecture (public and/or private sector).
  • Strong leadership and mentoring abilities; able to support pre-sales and practice growth.
  • Proactive, self-starter with excellent problem-solving and communication skills.
  • Actively engaged with data standards, open-source communities, or industry forums.

Related Jobs

View all jobs

Senior Data Architect

Senior Data Architect

Senior Data Architect – Canary Wharf London (IT) / Freelance

Senior Data Architect

Senior Data Architect

Senior Data Architect (6449) - Cambridge

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.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

Why the UK Could Be the World’s Next Data Science Jobs Hub

Data science is arguably the most transformative technological field of the 21st century. From powering artificial intelligence algorithms to enabling complex business decisions, data science is essential across sectors. As organisations leverage data more rapidly—from retailers predicting customer behaviour to health providers diagnosing conditions—demand for proficiency in data science continues to surge. The United Kingdom is particularly well-positioned to become a global data science jobs hub. With world-class universities, a strong tech sector, growing AI infrastructure, and supportive policy environments, the UK is poised for growth. This article delves into why the UK could emerge as a leading destination for data science careers, explores the job market’s current state, outlines future opportunities, highlights challenges, and charts what must happen to realise this vision.