National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

VP Lead JAVA Software Engineer (Apply in minutes)

Barclays Bank
Cliftonville
9 months ago
Applications closed

Related Jobs

View all jobs

Chief Technology Officer

VP of Data Science - GenAI (relocate to UAE, tax free)

Manager, Data & Analytics, Global Insight

Senior Data Scientist - Speech-To-Text

Senior Data Scientist - Speech-To-Text

Vice President, Data Scientist

Join us as a VP Lead JAVA Engineer within the Core Services Team where you will be responsible for leading great engineering across our new platform services and products. An exciting opportunity for an experienced technologist, you will drive the delivery of our core cloud-based platform which is used by multiple client facing applications. To be successful as a VP Lead JAVA Engineer within this team, you should have: ● A track record of building enterprise-scale applications using Java and Spring Boot frameworks ● Experience building event-driven services using Kafka or similar technologies ● Comprehensive understanding of API and Microservice design patterns backed up by experience delivering and running the services you have built in production ● Solid understanding of DevOps, CICD pipelines and software quality metrics You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills. This role will be based out of our Northampton office. Purpose of the role To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure. Accountabilities ● Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data. ● Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures. ● Development of processing and analysis algorithms fit for the intended data complexity and volumes. ● Collaboration with data scientist to build and deploy machine learning models. Vice President Expectations ● Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment. ● Manage and mitigate risks through assessment, in support of the control and governance agenda. ● Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does. ● Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business. ● Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies. ● Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions. ● Adopt and include the outcomes of extensive research in problem solving processes. ● Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

National AI Awards 2025

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.

Machine Learning Jobs Skills Radar 2026: Emerging Tools, Frameworks & Platforms to Learn Now

Machine learning is no longer confined to academic research—it's embedded in how UK companies detect fraud, recommend content, automate processes & forecast risk. But with model complexity rising and LLMs transforming workflows, employers are demanding new skills from machine learning professionals. Welcome to the Machine Learning Jobs Skills Radar 2026—your annual guide to the top languages, frameworks, platforms & tools shaping machine learning roles in the UK. Whether you're an aspiring ML engineer or a mid-career data scientist, this radar shows what to learn now to stay job-ready in 2026.

How to Find Hidden Machine Learning Jobs in the UK Using Professional Bodies like BCS, Turing Society & More

Machine learning (ML) continues to transform sectors across the UK—from fintech and retail to healthtech and autonomous systems. But while the demand for ML engineers, researchers, and applied scientists is growing, many of the best opportunities are never posted on traditional job boards. So, where do you find them? The answer lies in professional bodies, academic-industry networks, and tight-knit ML communities. In this guide, we’ll show you how to uncover hidden machine learning jobs in the UK by engaging with groups like the BCS (The Chartered Institute for IT), Turing Society, Alan Turing Institute, and others. We’ll explore how to use member directories, CPD events, SIGs (Special Interest Groups), and community projects to build connections, gain early access to job leads, and raise your professional profile in the ML ecosystem.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.