Specialist: Data Architecture at Absa Group Limited (Absa)

Job Summary

• The Data Architect is responsible for designing, governing, and optimizing the data architectures that enable analytics, operational systems, regulatory reporting, and enterprise data platforms within the bank. The role focuses on defining end-to-end data design - spanning ingestion, storage, modelling, transformation, distribution, and consumption - ensuring that solutions are scalable, secure, compliant, and aligned with enterprise standards.
• The Data Architect works closely with information architecture, data engineering, business units, and solution architecture to deliver data solutions that power high-quality insights, enable advanced analytics, and support mission-critical banking processes.

Job Description

Role Purpose 

• The Data Architect is responsible for designing, governing, and optimizing the data architectures that enable analytics, operational systems, regulatory reporting, and enterprise data platforms within the bank. The role focuses on defining end-to-end data design - spanning ingestion, storage, modelling, transformation, distribution, and consumption - ensuring that solutions are scalable, secure, compliant, and aligned with enterprise standards. 
• The Data Architect works closely with information architecture, data engineering, business units, and solution architecture to deliver data solutions that power high-quality insights, enable advanced analytics, and support mission-critical banking processes. 

2. Key Responsibilities 

Data Architecture Design 

• Develop conceptual, logical, and physical data architectures supporting operational systems, analytics, and regulatory reporting. 
• Design end-to-end data flows including ingestion, transformation, storage, integration, and output models. 
• Define data models, schemas, and structures aligned to enterprise information architecture and canonical models. 
• Create architecture blueprints, data pipeline designs, and integration patterns (e.g., streaming, batch, event-driven). 
• Ensure data solutions meet NFRs including performance, reliability, scalability, and security. 

Platform & Solution Enablement 

• Collaborate with platform teams to shape the bank’s cloud and on-prem data platforms (e.g., data lakehouse, MDM, metadata catalog, streaming). 
• Guide data engineers on best-practice patterns for ETL/ELT, distributed processing, storage optimization, and schema evolution. 
• Influence the selection and configuration of data processing frameworks, and tooling. 
• Support BU-aligned delivery teams by translating business requirements into robust data architecture designs. 

Governance, Standards & Quality 

• Ensure data architectures comply with enterprise standards, data governance requirements, and regulatory obligations (POPIA, AML/KYC, retention policies). 
• Establish and maintain standards for data modelling, data lifecycle management, lineage, and monitoring. 
• Promote the adoption of reusable data assets, common data domains, and golden sources. 
• Participate in solution reviews, architecture governance forums, and design assurance activities. 

Collaboration & Stakeholder Engagement 

• Partner with Information Architects, Solution Architects, Business Architects, Data Engineers, and Analysts to drive coherent end-to-end solutions. 
• Engage with business stakeholders to understand domain context, ensuring data requirements are reflected accurately in technical designs. 
• Serve as a trusted advisor to BU teams on data-related design decisions. 

Innovation & Future-State Architecture 

• Contribute to the definition of the bank’s data architecture target state, focusing on modernization, simplification, interoperability, and automation. 
• Advocate modern data concepts: data products, federated domain-oriented data ownership, event-driven integration, and open table formats (Parquet/Iceberg). 
• Evaluate emerging technologies and propose evolution paths for the bank’s data ecosystem. 

3. Required Skills & Experience 

Technical Skills 

• Strong experience in data modelling (conceptual, logical, physical) across relational, dimensional, and NoSQL paradigms. 
• Deep understanding of data engineering principles and technologies (e.g., SQL, Spark, Kafka, Flink, Airflow). 
• Proficiency with cloud-based data platforms (AWS, Azure) and hybrid/on-premise environments. 
• Expertise with data warehouses, data lakes, and lakehouse architectures. 
• Familiar with metadata/catalog tools, governance frameworks, and data quality tooling. 
• Knowledge of integration patterns (ETL/ELT, API-based, stream processing, microservices). 
• Experience in designing high-volume, high-throughput, and low-latency data architectures. 

Soft Skills 

• Strong communication skills with both technical and business stakeholders. 
• Ability to simplify complexity and explain technical concepts in business-friendly language. 
• Effective collaborator with a track record of influencing decision-making across federated teams. 
• Analytical thinker with strong problem-solving skills and architectural discipline. 

4. Qualifications 

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field. 
• Professional certifications advantageous: AWS/Azure Data Architect, Databricks. 
• 7+ years of experience in data architecture, data engineering, or solution architecture roles—preferably within banking or other highly regulated sectors. 

5. Key Outcomes & Measures of Success 

• Delivery of high-quality, scalable data architectures adopted across BU and group teams. 
• Performance, reliability, and resilience improvements across data pipelines and platforms. 
• Increased standardisation and decreased redundancy of data solutions. 
• Strong alignment between data architecture, information architecture, and solution architectures. 
• Compliance with governance and regulatory requirements with traceable lineage and controls. 
• Improved ability of business teams to access trusted, well-structured data for analytics and reporting. 

6. Working Model 

• Hybrid working arrangement. 
• Active participation in Architecture Council, Data Governance Board, and design authority sessions. 
• Frequent engagement with engineering teams to provide hands-on architectural direction. 

Education

• Bachelor`s Degrees and Advanced Diplomas: Data Science, Bachelor`s Degrees and Advanced Diplomas: Information Technology

End Date: December 15, 2025