Solutions Architect

Solihull
1 year ago
Applications closed

Related Jobs

View all jobs

GCP Data Architect

GCP Data Architect

Data Architect

Data Warehouse Architect

Data Engineer

Data Engineer

Purpose of the Role:

The Solutions Architect will lead the creation of the overall business systems architecture and processes, the application of agreed development and service design principles. The scope includes all customer facing systems (online, mobile, and on-site), plus all IT systems used by our colleagues in sites, head office, and field-based teams.

Duties and Responsibilities:

Translate business requirements into IT solutions, considering the complexity of existing IT systems, business priority and scope of requirements.

Provide technical leadership and direction across the IT teams for all technical solutions being implemented

Create and maintain a full set of roadmaps covering technology, applications, and services

Establish and agree a data model to support the management and operation of our business and supporting systems with the Data Architect.

Contribute to and agree the Infrastructure Roadmap with the Infrastructure Team.

Align all plans and proposals with their corresponding Business Plan components

Ensure all data controls, systems and services adhere to the agreed compliance standards set out by the Security team.

Work with Business change team, and key stakeholders to successfully monitor progress of initiatives.

Contribute to the creation of business cases to support all proposed investments

Research industry and technology trends while being able to identify opportunities to advance our customer proposition and internal operations.

Create and maintain architectures for new and existing solutions which support the IT strategy and are aligned with Stonegate’s architecture principles.

Skills, Experience and Qualifications:

Essential:

Extensive, relevant experience in Architecture and/or IT development/analysis

Extensive, relevant experience of managing suppliers at a senior level

Experience of working in a B2C, customer focussed company

A good communicator able to create accurate and informative summaries of complex updates/issues

Thinks both laterally and holistically – can “connect the dots” between the big picture and the detail

Highly comfortable with standard architecture, development, and operational principles and technologies/tools

Ability to turn business problems into solution design

Strong verbal and written communication skills

Desirable:

Hospitality/retail experience highly desirable

Educated to degree standard or equivalent (or appropriate practical experience)

TOGAF-certified/aware

User knowledge of Ardoq

What's in it for you? 

25 days annual leave

Annual Leave Purchase Scheme

Pension

Vitality Healthcare

Opt in dental insurance programme

Annual bonus scheme

The Stonegate discount card offering discounts across our managed estate

Online benefits portal offering discounts across the High Street and other retailers

At Stonegate Group, we're proud to be the biggest operator of pubs, bars, and late-night venues in the United Kingdom. Our leading brands are diverse and well-known, including names like Slug & Lettuce, Be At One and Popworld. Find out more about a career with Stonegate Group at .

If you have a disability as outlined by the Equality Act 2010 and require reasonable adjustments to be made during the recruitment process, please let us know in advance so that any support, aids or adaptations can be put in place to assist you. Please contact (url removed).  #LI-HR1

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.

Careers

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.

Jobs

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.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.