Software Development Team Lead - Regulatory Data

As a Regulatory Data Team Leader, you will lead a cross-functional team in the delivery of regulatory reporting software solutions. The Data Engineering department is responsible for writing software and reporting systems to communicate jurisdiction-specific information to international regulators. They are developed to high standards, tuned for performance and reliability with low tolerances for error. We're using an architecture that includes high-throughput, database-centric distributed applications, that supports batch reporting, integrates with SOAP and REST APIs, and features Windows and web services, as well as web applications. You will be responsible for ensuring the team's output meets stringent regulatory reporting requirements while upholding high standards of technical design. This role is eligible for inclusion in the Company’s hybrid working policy. - Strong experience with GCP and BigQuery, demonstrating a deep understanding of cloud architecture. - Experience working with various AI tools to enhance workflows and processes, demonstrating a practical application of AI in projects. - Experience of leading a geographically distributed software delivery team. - Highly organised and adaptable; adept at prioritisation, delivery, and driving efficiency in a high-throughput and fast-paced environment. - Maintain a positive outlook whilst adapting to rapidly changing requirements. - Experience of driving collaboration across key stakeholders to ensure requirements are clarified, solution designs are produced and implemented within the required timeframes. - Start up mindset with excellent communication and interpersonal skills that inspire and motivate teams. - Experience in the design and implementation of software solutions within a cloud architecture would be advantageous. - Experience of working within a regulatory or commercial gambling environment. - Commercial database development experience coupled with optimisation skills, using SQL Server 2014 or later, T-SQL, or BigQuery and GoogleSQL.