Senior Manager, Data Architect

Overview

Leading investment financial services firm, renowned for its innovative investment strategies, strong market presence, and commitment to technological excellence.

• Data Architecture Strategy: Define and evolve the firm's enterprise data architecture strategy, including data governance, data lifecycle management, data security, and data quality frameworks, aligned with business objectives and regulatory requirements.
• Architectural Design & Oversight: Lead the design and implementation of scalable, robust, and high-performance data architectures for transactional systems, data warehouses, data lakes, and analytical platforms, ensuring architectural integrity across all data initiatives.
• Data Modelling Expertise: Provide expert guidance and hands-on contributions to logical and physical data modelling for complex financial datasets, ensuring optimal database design, data integrity, and performance for various applications.
• Technology Evaluation & Selection: Evaluate and recommend appropriate data technologies, tools, and platforms (e.g., relational databases, No
  
  SQL, data warehousing solutions, cloud data services, streaming platforms) that best fit the firm's architectural vision and business needs.
• Vendor & Consulting Firm Management: Collaborate effectively with external technology vendors and consulting firms, overseeing their contributions to data architecture projects and ensuring alignment with the firm's strategic data roadmap.

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related quantitative field.
• Minimum of 10+ years of progressive experience in data architecture, data engineering, or a related field, with at least 4 years in a senior architect or leadership role within the financial services or investment sector.
• Exceptional and demonstrated experience in data modelling (conceptual, logical, and physical), schema design, and database normalisation/denormalisation techniques, with a strong understanding of their impact on performance and scalability.
• Extensive experience across the breadth of data architecture domains including data warehousing, data lakes, ETL/ELT processes, data governance, metadata management, and data security.