Fusion People
Enterprise Data Architect (AI Data, MDM, Data Strategy)

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Job Title: Enterprise Data Architect
About the Role
My client, a leading multinational, is looking for an Enterprise Data Architect to play a critical role in designing and evolving the global data landscape and to establish the roadmap and transition for the data architecture future state. We need a true Data Architect, not a Solution Designer or Engineer but a Data Architect who knows how to ask the right questions, who understands ‘What is needed’, ‘Why it is needed’ and can produce the building blocks for the Solution Designers to bring to life and bring people on the data journey unlocking opportunities within data across the organisation.
Core Focus
- C-suite engagement and communication
- Enterprise data strategy and roadmap ownership
- AI-ready data architecture (governance, classification, control)
- MDM across core domains (Client, Matter, Finance, People)
Responsibilities
- You will report to the Head of Data and be responsible for the following:
- Drive and evolve the global Data Architecture roadmap in alignment with Enterprise and Data Architecture strategy
- Own the enterprise data model and establish data architecture patterns and standards for data modelling, integration, storage, and governance.
- Provide technical leadership across data platforms, pipelines, and analytics capabilities.
- Partner with data security and data governance to define frameworks, data classification, privacy, data governance ownership, stewardship
- Be the senior voice on data design decisions across major projects
- Champion data architecture and bring the organisation on the journey bridging gaps between different teams across Data Governance, Platforms and Product capabilities.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Skills & Experience


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- Experience of Data Architecture and partnering with business leaders across Corporate Functions (IT, HR, Finance, Legal) to drive the data agenda and establish best in class data architecture.
- Essential experience in Azure Data Services to design target architecture for data platforms including Azure Data Lake, Synapse Analytics, Databricks, Data Factory, Azure Service Bus, Azure SQL and APIs)
- Essential experience in architecting data pipelines and data integration patterns
- ETL/ELT processes, and real-time streaming architectures.
- Master Data Management (e.g. Informatica, Profisee, SAP)
- AI data requirements would be beneficial as well as experience on Microsoft stack including Copilot
- Data modelling and dimensional modelling
- Experienced in BI / Analytics tools (Power BI, Tableau)
- Data integration patterns such as APIs, messaging (Service Bus), and ETL/ELT.
- Enterprise Architecture tools e.g. LeanIX, Ardoq
- TOGAF and Azure Certification (strong nice to have)
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