Enterprise Data Architect - Oracle Fusion

London
2 months ago
Create job alert

Enterprise Data Architect - Oracle Fusion

London - 2 days day/week onsite

24 month project

We are looking for an experienced Enterprise Data Architect to lead the design, governance, and optimisation of data across their new Oracle Fusion Cloud environment.

You will be joining an established organisation who are embarking on a digital transformation.

This is a senior, hands‑on role working closely with business stakeholders, functional consultants, and technical teams to shape data strategy and support both transformation and BAU operations.

Key Responsibilities:

Own the end‑to‑end data architecture for Oracle Fusion Cloud applications

Design and govern data models, data flows, and integration patterns across Fusion modules

Define and enforce data standards, quality rules, and master data management principles

Lead data migration activities including data mapping, cleansing, validation, and reconciliation

Provide architectural oversight for integrations using OIC, REST/SOAP APIs, and third‑party systems

Support reporting and analytics using OTBI, BI Publisher, and downstream data platforms

Act as a subject‑matter expert for Oracle Fusion data structures and release impacts

Collaborate with security, functional, and testing teams to ensure compliant and reliable data usage

The role will be based out of their London office with occasional travel to sites in the UK

Related Jobs

View all jobs

Enterprise Data Architect

Enterprise Data Architect - Oracle Fusion

GDPR Data Architect

Principal Data Architect DV Cleared

GDPR Data Architect

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.