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

Apply Now

Data Engineer

Barclays Bank PLC
Glasgow
9 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer Data Science/Java/Python/Unix

Data/Machine Learning Ops Engineer

Data/Machine Learning Ops Engineer

Data Science Engineer

Data Scientist / Quant Engineer

Data/Machine Learning Ops Engineer

Join us to build the next-gen Advanced Data and Analytics Platform. We are looking for a dedicated and experienced Data Engineer with very good ETL/ELT and Data Warehousing skills, to work in a collaborative and friendly team on exciting automation deliveries, on premise and in cloud. As a Data Engineer, you’ll be responsible for the build and delivery of the Ops Analytics Platform across a number of hosting platforms building robust, scalable data pipelines. You will be automating the deployment and maintenance of the Advanced Analytics Platform using the latest and greatest technologies and CI/CD tools such as dbt, GitLab etc. You will also deliver self-service capabilities and automations to enable easy adoption of the Ops Advanced Analytics Platform. Key skills required for this role include:Proficiency in Python and SQL is critical for data manipulation and building data pipelinesAbility to design and maintain robust ETL/ELT processesStrong experience in managing and optimizing data warehouses (e.g., Snowflake, Redshift)Additional skills include:Expertise in cloud platforms such as AWS, Azure, or GCP for modern data solutionsHands-on experience with big data frameworks like Apache Spark or HadoopExperience with tools for pipeline automation and monitoring (e.g., Airflow, Prometheus)You may be assessed on 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. The role is based out of our office in Glasgow.Purpose of the roleTo 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.Analyst Expectations· Will have an impact on the work of related teams within the area.· Partner with other functions and business areas.· Takes responsibility for end results of a team’s operational processing and activities.· Escalate breaches of policies / procedure appropriately.· Take responsibility for embedding new policies/ procedures adopted due to risk mitigation.· Advise and influence decision making within own area of expertise.· Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct.· Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function.· Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.· Make evaluative judgements based on the analysis of factual information, paying attention to detail.· Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents.· Guide and persuade team members and communicate complex / sensitive information.· Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation.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

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 Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

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.