A Data Architect is responsible for designing and implementing data frameworks that allow businesses to manage and use their data efficiently. They work with stakeholders – from other data specialists to security and compliance teams to senior business executives and leadership – to define data strategies, ensure data quality, and optimise database structures. A Data Architect’s role often intersects with data engineering, business intelligence, and cloud computing, requiring both technical expertise and strategic thinking.

A typical Data Architect is involved in several key areas:

Data Strategy & Governance:

• Define how data is collected, stored, and accessed across the organisation, ensuring compliance with industry regulations and best practices.
• Execute on Data Architecture roadmaps and implement data frameworks, ensuring corrective actions are taken where necessary.
• Contribute to information architecture platforms and ensure alignment with Enterprise Data Model (EDM) frameworks and enterprise data warehouses (EDW).
• Drive profitability and cost efficiencies through enhanced data practices and agile methodologies.
• Monitor data operations and uphold high standards of data ethics and governance.

Database Design & Development:

• Create efficient, scalable, and secure database structures, including relational (SQL) and non-relational (NoSQL) systems.
• Develop and optimise data pipelines, models, and database schemas aligned to strategic data platforms.
• Support decommissioning of non-compliant infrastructure to maintain adherence to architectural principles.
• Guide the development of organisational Business Intelligence (BI) and Management Information Solutions (MIS).

Data Integration & ETL Pipelines:

• Design and manage Extract, Transform, Load (ETL) processes to ensure seamless data flow and consistency across systems.
  Ensure that solutions adhere to principles such as non-duplication of data (e.g., master data and reference data management).
  Support advanced model deployment with reusable, aligned data pipelines and constructs like feature stores.

Cloud & Big Data Solutions:

• Implement cloud-based solutions (e.g., AWS, Azure, Google Cloud) that support big data analytics and real-time processing.
  Evaluate and adopt emerging technologies to simplify and enhance the data architecture landscape.

Security & Compliance:

• Ensure implementation of data security measures (e.g., encryption, access control) and regulatory compliance (e.g., GDPR, POPIA).
• Align with IT Risk and Governance standards including SDLC, change management, and release management.

Collaboration & Cross-functional Leadership:

• Partner with business leaders and technical teams to assess and meet data architecture requirements.
• Collaborate with data engineers, modellers, platform leads, and solution architects to ensure coherent and scalable solutions.
• Promote awareness and provide training on data architecture frameworks and principles.
• Participate in committees to ensure compliance with data architecture standards and contribute to a unified enterprise architecture.

Innovation & Continuous Improvement:

• Keep abreast of technological advancements and evolving best practices to future-proof data systems.
• Continuously identify patterns, trends, and gaps to propose and implement best-fit solutions.
• Drive the adoption of strategic data platforms, and reduce duplication and inefficiencies in data operations.