Join Barclays as a Senior R&D Software and Data Engineer where 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.Python, PHP, JavaScript, Java, Relational databases (Postgres, MS SQL, Oracle, MySQL, etc.), SAS PROC SQL, Hue Database Assistant, Teradata, and non-rational Hadoop. 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.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.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.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.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).Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.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.
