Principal Data Architecture Lead

About the role

The Principal Data Architecture role will define and drive the bank's enterprise data architecture across data platforms, integration, ETL/ELT, analytics and AI. It combines strategic architecture leadership with hands‑on development and production deployment responsibilities.

Key responsibilities

• Define and evolve enterprise data architecture, standards, reference models and technology roadmap for operational, warehouse and analytical platforms.
• Lead end‑to‑end solution architecture for major data‑intensive initiatives, translating business and regulatory requirements into secure, scalable designs.
• Architect, design and contribute to robust ETL/ELT pipelines, ensuring standards for ingestion, reconciliation, error handling, monitoring and performance.
• Embed data governance, lineage, metadata, privacy and security controls into solution designs to meet banking regulatory requirements.
• Review and approve solution and detailed designs, establish reusable patterns and drive standardisation and modernisation.
• Partner with architects, security, infrastructure, data‑governance and business stakeholders; mentor technical teams and lead architecture workshops.

Required profile

• Bachelor’s degree in IT, Computer Science, Engineering or related field; postgraduate qualification advantageous.
• 10‑14 years of relevant experience, including extensive data architecture and complex solution design.
• Proven experience leading architecture across multiple domains or large transformation programmes.
• Architecture certifications such as TOGAF are a plus.

Required skills

• Data architecture and data modelling (relational, dimensional, analytical).
• ETL/ELT development and data integration (Oracle Data Integrator, SQL Server Integration Services, Change Data Capture).
• Advanced SQL and PL/SQL development, including stored procedures, views, functions and partitioning.
• Database administration, performance optimisation and production support.
• Strong understanding of data governance, security, privacy and regulatory compliance in banking.
• Experience with AI/Generative AI integration within data engineering and analytics.