Data Architect

DLA Piper International LLP
Leeds
3 days ago
Create job alert

The Data Architect will define solutions and processes for managing enterprise-wide data throughout the data lifecycle from capture to processing to usage across all layers of the architecture.


The Data Architect will work with business users, I.T. delivery teams, and Project Mangers to deliver solution architectures that aligns with the Enterprise data strategy and vision. Must develop a strong understanding of each business unit to include their business drivers for success, process and approaches to business models.


The role will focus on defining, developing and promoting the Solution Architectures that aids the organisation in building out the Enterprise Data vision.


Main duties and responsibilities

  • Define solution architectures for Data Warehouse, Master Data/Reference Data and integration for data
  • Contribute to the creation of an Enterprise Reference Data Architecture for the business
  • Participation in the definition of standard enterprise data management and enterprise data architecture processes and deliverables
  • Collaboration with the business, its applications, solutions, and with other IT architects to understand the implications of respective architectures on data architecture and to maximize the value of information across the organisation
  • The creation and implementation of processes to collect and maintain inventory of Data assets across the enterprise
  • Assist in maintaining the assessment and inventory of the existing enterprise-level data environment
  • Assist in defining MDM solution architecture and set technical direction, define component architecture, review detailed designs for accuracy and overall compliance to defined architecture
  • Analyse and define detailed MDM processes, tasks, data flows, and dependencies
  • Define the solution architecture and design for data management to ensure effective delivery of information that meets current and future requirements
  • Works with business process experts to help identify functional requirements
  • Analyses impact of future topology changes in the environment
  • Facilitate system feasibility studies, proof of concepts, pilot project, and testing while working with stakeholders to define business and systems requirements in a modern data architecture
  • Develop, implement, and maintain all data management policies and procedures, including those for enterprise data warehouse architecture, standards, monitoring, and service provision
  • Verify design of overall Infrastructure and support the build of the environments

EA Compliance

  • Oversee the documentation of all architecture design and analysis work
  • Consult with infrastructure, project and product teams to ensure consistency with the enterprise architecture, as well as to identify when it is necessary to modify the enterprise architecture

About you

  • Good knowledge of Third Normal Form data modelling
  • Consistently demonstrate strong experience in Conceptual, Logical, and Physical Database architectures, design patterns, best practices, and programming techniques around relational modelling, dimensional modelling and data integration
  • Experience in driving Meta data architecture and Master Data Management Solutions
  • Experience in performing analysis and design for Data Management and Data Driven projects
  • Awareness of MDM trends, MDM concepts and other tools in the market
  • Strong understanding of activities within primary discipline such as Master Data management (MDM), Metadata Management and Data Governance (DG)
  • Experience of Cloud Data technologies, solutions and future Cloud Data Strategies
  • Able to review designs independently, lead code reviews and ensure quality throughout the life of each project
  • Experience of enterprise systems data requirements and challenges would be beneficial, e.g. SAP, Salesforce
  • Ability to translate and clearly formulate technical issues and solutions to the issues
  • Excellent problem solving and analysis skills
  • Excellent communication skills - written and verbal
  • Excellent presentation skills
  • Intervenes if warning signs of problems occur within own area of responsibility
  • Forward thinking. Proactive rather than Reactive
  • Strong leadership and influence skills across Business and Technology organizations
  • Hands on experience of Microsoft Azure technology stack, such as Azure Data Factory, Synapse Data Warehouse, Power BI, ADLS, Data Bricks, SSRS, Microsoft Fabric, etc.
  • Hands on experience of SAP Data and BI technology stack, such as HANA database, SAP IQ database, Business Objects Data Services, SAP Data Intelligence, Business Objects, SAP Analytics Cloud, etc


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Architect

Data Architect

Data Architect

Data Architect – Multi-Cloud – Eligible for Security Clearance

Data Architect - Halifax; Home Based

Data Architect

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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

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.