Lead Architect

KPMG
Sheffield
11 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Architect | Snowflake & AWS | £130k | Roadmap to Head of Engineering

Senior Data Architecture Lead - Hybrid, Public Sector

Remote Data Architect - Strategic, Cloud & AI Lead

Remote Data Architect — AI Analytics & Cloud DW

Senior Data Architect — Secure Defence Data Platforms

Big Data Architect

The Role

 

We’re looking for an experienced architect to join the Audit technology team.

 

The lead architect will be responsible for designing and implementing the overall audit architecture strategy to ensure alignment with business goals and objectives. This role involves analysing the current technology infrastructure, identifying areas for improvement, and developing plans to enhance efficiency, scalability, and security. You will need to understand our Audit technology strategy and collaborate with stakeholders, technology teams, and vendors, to develop comprehensive architectural solutions that support the Audit strategy.

The individual will report to the Head of Technology & Solutions.

 

Responsibilities

 

Develop and maintain the Audit architecture strategy, ensuring alignment with business objectives and technology trends, collaborating with Enterprise-Wide Technology and global audit. Build and maintain collaborative relationships with business and technology stakeholders to understand their requirements and translate them into architectural designs. Conduct analysis of the existing technology infrastructure, identify gaps, and propose solutions to improve efficiency, reliability, and security. Define and document the Audit architecture framework, including principles, standards, and guidelines for technology selection and implementation. Collaborate with project teams to ensure that architectural guidelines and best practices are followed during the development and implementation of technology initiatives. Create architectural blueprints, diagrams, and models to communicate the vision and guide the implementation of enterprise solutions. Evaluate emerging technologies and industry trends to identify opportunities for innovation and provide recommendations for their adoption. Lead the evaluation, selection, and integration of third-party solutions and services, ensuring compatibility with existing systems and alignment with business needs. Conduct regular reviews and audits of the architecture to identify areas for improvement and ensure ongoing compliance with standards. Provide technical guidance and mentoring to other IT teams and stakeholders on architectural matters. Foster effective collaboration in multi-disciplinary teams. Understand implications and trade-offs of reliability, scalability, security, operation costs, adoption path recruitments.

 

Experience & skills

 

Strong knowledge of architecture frameworks. In-depth understanding of a broad spread of technology domains, including application architecture, data architecture, infrastructure architecture, and security architecture. Experience in conducting technology assessments, gap analysis, and developing roadmaps for technology transformation. Proficiency in creating architectural diagrams and models using industry-standard tools. Strong analytical and problem-solving skills, with the ability to translate business requirements into practical architectural designs. Excellent communication and interpersonal skills, with the ability to effectively collaborate with stakeholders at all levels of the organization. Knowledge of cloud computing platforms, microservices architecture, and modern development practices is desirable. Relevant certifications, such as TOGAF, AWS Certified Solutions Architect, or Microsoft Certified: Azure Solutions Architect, are beneficial but not required.

 

People & Culture

 

Embrace and embed our culture ambition of high challenge, high support which is grounded in Our Values. Operate with a curious and sceptical mindset ensuring that this is embedded in your everyday work. Actively lead and embed a coaching culture to get the best out of others in an environment where everyone in the team feels empowered to speak up or challenge where appropriate. Be inclusive and embrace the opportunity to work with other teams within Audit and across the firm in an integrated way. Have a sense of community, purpose, and fun.

 

#LI-DC1

 

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.

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.

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.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.