Are you passionate about data and analytics? Our leading client is seeking a Data Warehouse Manager to lead a dynamic team in delivering cutting-edge data warehousing solutions. This role involves supporting day-to-day operations and driving the modernization of our data warehousing function to utilize industry-leading tools within a modern cloud architecture. The successful candidate will have strong data warehouse experience in data-related development roles, including SAS, ETL and Python. Key Responsibilities: Team Leadership: Coordinate and manage the data warehousing team to deliver support and change requirements. Work Management: Track and manage the data warehousing work backlog, prioritizing tasks as agreed with technology management. People Management: Mentor and develop team members, fostering a collaborative and innovative environment. Technical Delivery: Deliver ETL and data processing code as part of a working technical team. Process Automation: Develop and maintain process automation solutions. Vendor Liaison: Work with third-party suppliers and vendors to ensure productive relationships. Documentation: Ensure data warehousing systems and processes are adequately documented. Security & Compliance: Advise on data security and compliance requirements. Solution Design: Ensure the right architecture, process, and code structure for changes or new developments. Scheduling Support: Maintain and support the scheduling system for reporting and warehouse build jobs. Best Practices: Champion coding and solution design best practices within the data warehousing user community. Skills & Qualifications: Educational Background: Degree in Computer Science, Engineering, Mathematics, or a related field. Team Management: Experience managing a technical team (desirable). Communication: Excellent client-facing, written, and verbal communication skills. Technical Skills: Strong understanding of data warehousing and ETL principles. Experience with SAS software on a SAS 9.4 platform. Knowledge of Oracle database solutions and other platforms (SQL Server, etc.). Proficiency in Python 3.x. Intermediate skills in Windows and Linux OS, including batch/shell scripting. Organizational Skills: Attention to detail and multi-tasking abilities. Problem-Solving: Strong analytical and problem-solving skills. Sector Knowledge: Understanding of the finance sector and legal guidelines around data and finance.