Senior R&D Software and Data Engineer

Barclays Bank PLC
Northampton
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Machine Learning Developer

Senior Data Scientist, Quantitative Biosciences ...

Senior Data Scientist

Undergraduate Intern - Data Science

Join Barclays as aSeniorR&D Software and Data Engineerwhere you'll spearhead the evolution of our digital landscape, driving innovation and excellence. In this role, you will be an integral part of our Cyber Fraud Fusion Centre, delivering scalable CFFC services to disrupt and prevent upstream economic crime.

To be successful as a Senior R&D Software and Data Engineer, you will need the following: 

  • Experience working within Financial Service teams responsible for cyber fraud, financial crime, or security (web/app).
  • Experience with industry fraud and security signals, including any such as digital identity, device, voice, biometrics, and behavioural profiling technologies.  
  • Knowledge of malicious attack vectors used by cyber fraud adversaries to target the financial sector including but not limited to Device Spoofing, Location Manipulation, Identity Fraud, Account Takeover and False documentation.
  • Development experience and/or experience using analytical tools: Python, PHP, JavaScript, Java, Relational databases (Postgres, MS SQL, Oracle, MySQL, etc.), SAS PROC SQL, Hue Database Assistant, Teradata, and non-rational Hadoop.

Some other highly valued skills may include: 

  • Experience working within Financial Service teams responsible for cyber fraud, financial crime, or security (web/app). Advanced knowledge of malicious attack vectors used by cyber fraud adversaries.
  • Knowledge of Enterprise security frameworks such as NIST Cybersecurity Framework and Cyber-attack phases.
  • Previous advanced experience using analytical tools and platforms such as SQL/SAS/Hue/Hive Basic, Quantexa, Elastic Search, SAS and MI tools like Tableau and Power BI.
  • Technical experience or advanced knowledge of computing, computer science and networks.

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.

The successful candidate can either be based inKnutsfordorNorthampton.

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.

Assistant Vice President Expectations

  • Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
  • Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
  • Take ownership for managing risk and strengthening controls in relation to the work done.
  • Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
  • Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
  • Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
  • Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
  • Influence or convince stakeholders 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.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!