Data Architect
The Data Architect designs systems to facilitate access to and finding of information. He/She plans, designs, develops and tests internal information-delivery solutions and data models with the focus on providing positive user experience. He works with end users to specify requirements, create and implement designs to meet internal and client-facing objectives. He develops information management standards and practices, in compliance with data privacy policies and ethics and governance frameworks. He works in a team setting and is proficient in database systems, scripting and programming languages required by the organization. He is also familiar with the relevant software platforms on which the solution is deployed on. The Data Architect integrates diverse needs and perspectives from internal and external clients, and possesses a creative mind to develop new and fresh ideas and solutions. He possesses strong leadership and communication abilities and is able to influence key stakeholders and clients he interfaces with.
Skills and Competencies
Technical Skills & Competencies
Generic Skills & Competencies
Critical Work Functions and Key Tasks
• Determine data engineering requirements across all systems,
platforms and applications based on artificial intelligence solutions
• Advise the business on data requirements based on information
and insights desired
• Establish and implement data ethics, privacy and security guidelines and policies
for potential new business cases that involve data engineering processes
• Advise on latest machine learning libraries, strategies, and products in database
and data processing software based on business requirements
• Define the desired state of information flow through the
organisation to determine the organisation’s data architecture
• Assess existing systems to evaluate their usability, usefulness,
visual design and content
• Guide alignment of information management standards with
the enterprise architectural plan and information security standards
• Develop strategies for seamless and low-risk migration of data between systems
• Communicate the data architecture design and recommendations to
stakeholders
• Formulate strategies for code compilation for model production
• Formulate AI/ML development pipeline strategies and infrastructure
for the organisation
• Provide technical guidance for scaling and pre-deployment of AI/ML model
• Create deployment blueprints for AI/ML models
• Provide technical guidance for deployment and optimisation of AI/ML models
• Ensure deployed AI/ML models are aligned with the organisation's core values
and comply with data governance and ethics guidelines
• Review operational strategies, policies and targets across teams and projects
• Develop strategies for resource planning and utilisation
• Review the utilisation of resources
• Oversee the development of learning roadmaps for teams and functions
• Establish performance indicators to benchmark effectiveness of learning
and development programmes against best practices
• Implement succession planning initiatives for key management positions