Expert, Data Engineer

Key Accountabilities
Key Accountabilities (1)

RBG Data Mart Ownership

• Own and continuously enhance the RBG Data Mart architecture and roadmap.
• Design and maintain enterprise-grade dimensional data models and analytical datasets.
• Develop and govern business KPIs, metrics, and semantic layers to ensure consistency across reports and analytics.
• Ensure data quality, completeness, reconciliation, and traceability across analytical platforms.
• Collaborate with DA, IT, and business stakeholders to align analytical data solutions with enterprise standards and regulatory requirements.
• Drive continuous improvement of data architecture supporting Retail Banking analytics use cases.
  
  

Key Accountabilities (2)

BI Engineering & Analytics Solutions

• Translate business requirements into scalable BI and analytics solutions.
• Design, develop, and maintain ETL/ELT processes supporting RBG reporting and analytics.
• Build reusable data assets, analytical datasets, and reporting frameworks.
• Develop and optimize dashboards, scorecards, and management reporting solutions.
• Support self-service analytics capabilities through governed and business-friendly data products.
• Improve performance and automation of reporting and analytical processes.
  
  

Key Accountabilities (3)

Business Analysis & Solution Architecture

• Engage with business stakeholders to understand strategic objectives and analytical requirements.
• Lead requirement gathering, solution design, and impact assessment activities.
• Act as Solution Architect for RBG analytical initiatives.
• Recommend innovative data and analytics solutions to address business challenges.
• Ensure solutions are scalable, maintainable, and aligned with business priorities.
  
  

Key Accountabilities (4)

AI Enablement & Innovation

• Identify opportunities to leverage AI and Generative AI across Retail Banking operations.
• Build AI-enabled tools that support sales productivity, customer acquisition, customer servicing, campaign management, and business performance monitoring.
• Develop analytical data foundations required for AI and Machine Learning initiatives.
• Collaborate with Data Scientists, Technology teams, and business stakeholders to accelerate AI adoption.
• Promote AI-driven decision making through practical and measurable business use cases.
  
  

Key Accountabilities (5)

Project Leadership & Capability Building

• Lead end-to-end delivery of BI and analytics initiatives.
• Manage project scope, timelines, priorities, risks, and stakeholder expectations.
• Mentor junior BI Engineers and Analysts.
• Establish best practices in data modeling, BI development, analytics engineering, and AI adoption.
• Contribute to building a data-driven culture within RBG.
  
  

Key Relationships - Direct Manager
Senior Manager, Business Intelligence

Key Relationships - Direct Reports

Key Relationships - Internal Stakeholders
Members of Data Team - Private & Retail Banking Group; BAU Group stakeholders

Key Relationships - External Stakeholders
Partners and vendors providing professional services

Success Profile - Qualification and Experiences
Education

• Bachelor's or Master's degree in Computer Science, Information Systems, Statistics, Mathematics, Engineering, Data Analytics, or related disciplines.
  
  

Experience

• 7+ years of experience in Business Intelligence, Analytics Engineering, Data Warehousing, or Data Analytics.
• Proven experience designing and managing Data Marts and analytical data models.
• Strong experience in SQL, data transformation, ETL/ELT development, and data quality management.
• Hands-on experience with BI platforms such as Power BI, Tableau, or equivalent.
• Strong understanding of dimensional modeling, Star Schema, Snowflake Schema, and Data Warehouse concepts.
• Experience translating business requirements into analytical solutions and data products.
• Experience acting as Business Analyst, Product Owner, or Solution Architect in data and analytics projects.
• Good understanding of AI, Machine Learning, and Generative AI applications in business.
• Experience in Agile delivery environments.
• Banking or financial services experience is preferred.