Enterprise Data Architect

Role Objective

The Enterprise Data Architect will develop and manage the architecture for Big Data Analytics solutions, driving data analytics and Machine Learning applications. This role involves creating data models, establishing data architecture principles, and optimizing data delivery across both on-premises and cloud environments.

Key Responsibilities

• Collaboration: Work with DS&IT functions and business units to understand key business drivers and challenges.
• Data Architecture Development: Create data architecture models, roadmaps, and integrations to meet business needs.
• Standards and Policies: Define and maintain standards, processes, policies, and SLAs related to data architecture.
• Documentation: Develop and maintain data architecture documents and templates.
• System Integration: Collaborate on system integration and streamline business processes and data sources.
• Technology Advancement: Identify opportunities to leverage new technologies and trends.
• Project Support: Assist in data management system projects, including RFP preparation and resource alignment.
• Risk Management: Assess and mitigate data-related risks, maintaining a Data Control Risk Register.
• Data Governance: Contribute to data governance programs and ensure compliance with standards and regulations.
• Performance Measurement: Develop key performance measures for data integration and quality.
• Training and Awareness: Conduct training on data architecture processes and controls.
• Cross-functional Initiatives: Support business transformation and innovation initiatives.

Key Interactions

• Internal: CDIO, DS&IT department, strategy team, business units, internal audit, risk management, and others.
• External: Regulatory bodies, service providers, vendors, external auditors, customers, business partners, and alliances.

Competencies, Knowledge, and Experience

• Educational Qualifications: Degree in Computer Science, Information Systems, IT, Engineering, or related fields. A master's degree is an advantage.
• Experience: 10-15 years in financial services/banking with responsibilities in data architecture and transformation projects.
• Technical Competencies:
• Data warehousing, transformation, and modeling
• RDBMS (Oracle/SQL Server) programming
• Data governance principles
• IT security and data protection
• Emerging technologies and cloud computing
• Architecture governance and solution design
• Project management and stakeholder management
• Industry Knowledge: Trends, best practices, and regulatory compliance in the banking industry.
• Certifications: CDPSE, CDMP, or equivalent data architecture certification is mandatory.

Behavioral Competencies

• Leadership: Strategic thinking, performance management, decision-making.
• Delivering Results: Planning, problem-solving, research, and analysis.
• Operational Context: Resource management, adaptability, and change management.
• Organizational Success: Quality commitment, customer focus, continuous learning.
• Working with Others: Relationship management, respect, communication, and influence.