Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Big Data Solutions Architect (Hiring Immediately)

Barclays Bank PLC
Glasgow
10 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Senior Data Scientist - Defence

Senior Data Scientist - Defence

Senior Data Scientist

Senior Data Science Manager - Financial Planning and Analysis

Senior Data Scientist

As a Barclays Engineering Lead, you will get an exciting opportunity to createtechnology solutions to meet business requirements, in line with our grouparchitecture design standards and principles. You will be working directlywith the engineering director to design and deliver a group-wide strategicimplementation of a scalable API strategy with best of breed technologies.Lastly, you will be assisting in the development of systems strategy and plan.Essential Skills: * Strong understanding of data modelling techniques, including star schemas, normaliseddenormalised models and data warehousing solutions like Mongo DB, Couchbase, snowflake, or redshift.Desirable Skills: * Big Data Technologies with proficiencies in tools such as Apache Spark, Kafka, and cloud based data lake architecture (AWS, S3, Databricks SageMaker Feature Store) * Knowledge of Infrastructure as code tools (e.g Terraform, Cloudformation) to automate data infrastructure deployments to ensure repeatability and security * Skilled in workflow orchestration with tools like Apache Airflow or AWS step functions to manage data processes, automate tasks and ensure reliabilityGlasgowPurpose of the roleTo build and maintain the systems that collect, store, process, and analysedata, such as data pipelines, data warehouses and data lakes to ensure thatall 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 usdo what we believe is right. They will also be expected to demonstrate theBarclays Mindset – to Empower, Challenge and Drive – the operating manual forhow we behave.

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.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.