Enterprise Solution Architect

Hammersmith
1 year ago
Applications closed

Related Jobs

View all jobs

Principal Data Engineer (MS Azure)

SAS Data Engineer

Senior Data Engineer

Data Engineer

Senior Data Engineer

Data Engineer

Job Title: Enterprise Solutions Architect

Office Location with Hybrid Working: Hammersmith

Are you a seasoned Enterprise Solutions Architect ready to drive strategic alignment and innovation within a dynamic T&I organisation? This exciting role, reporting to the Director of Enterprise Architecture and Data, places you at the core of defining, evolving, and securing enterprise architecture, ensuring it meets business goals and exceeds expectations. This position combines end-to-end architectural leadership with a strong focus on stakeholder collaboration to achieve the highest standards of efficiency, security, and data integrity.

Location: Hammersmith, with hybrid working options

What Will You Be Doing?

Aligns the enterprise systems with the company's strategic vision
Works with business stakeholders to clarify and refine requirements aligned with business objectives
Contributes to the definition and ongoing maintenance of the Enterprise Architecture, using pragmatic application of TMF standards (e.g., eTOM process map and SID data model)
Takes ownership of one or more domains of the enterprise architecture (e.g., OSS, BSS) and works continuously to improve, focusing on efficiency, security, and data integrity
Acts as the architectural lead for key digital transformation programmes
Oversees and reviews design decisions to ensure consistency and alignment

What We Are Looking For

Proven experience in solution architecture, software development, business analysis, or similar domains
Stakeholder and supplier management, and mentorship experience
Proven experience in the ISP/Telco industry
Experience in implementing enterprise-level OSS/BSS solutions
Knowledge of Cloud Computing (e.g., AWS), Data Science, and generative AI
End-to-end experience of the Software Delivery Lifecycle, including Agile methodologies
Strong influence and stakeholder management skills
Strong drive and focus on results and delivery

Benefitts

Competitive salary
Global remote working for up to 2 weeks per year for those who are able to work remotely
25 days' paid holiday, increasing each year up to a maximum of 35 days
Extra days off for your birthday, moving home, wedding/civil partnership, and to volunteer
Private medical insurance provided by AXA Health
Life assurance covering 4 times your base salary
Partnership with the Kings Trust
Pension scheme matching contributions up to 4%
Retail offers - discounts from hundreds of recognised brands
Free broadband if you live in the service area
Enhanced pay for new parents

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 Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.