Zanaco Bank a leading financial services institution in Zambia, serving over 3 million customers and managing high volumes of daily transactions across multiple systems, is on a journey to harness the transformative power of Big Data, AI, and machine learning.
To drive this vision forward, the organisation is searching for a highly skilled Enterprise Data Architect to lead the transformation of its data infrastructure, unlocking scalable, data-driven insights that enhance decision-making, operational efficiency, and customer engagement.
Job responsibilities:
As the Enterprise Data Architect, you will:
- Lead Data Architecture Strategy: Oversee the organization’s data architecture, define sustainable strategies, and implement new data architecture frameworks.
- Design Scalable Data Solutions: Develop and implement solutions, such as data warehouses, data marts, and data lakes, tailored to the organization’s business needs.
- Manage Large Data Ecosystems: Build systems capable of handling large volumes of data, supporting storage, processing, and advanced analytics.
- Collaborate with Stakeholders: Engage with cross-functional teams to align data solutions with business objectives and drive innovation
Key Outputs:
- Develop a service culture – Develop a service culture which builds rewarding relationships, proposes innovations and allows others to provide exceptional client service.
- Process improvements and new innovations – Facilitate the conversion of knowledge and ideas into new or improved products for the data architecture.
- Costs containment – Cost Containment measured month-on- month on operational expenditure within control.
- Strategic planning – Define reference architecture, which is a pattern others can follow to create and improve data systems, translate business requirements into technical specifications, including data streams, integrations, transformations databases, and data warehouses.
- Project implementation – Define the data architecture framework, standards, and principles, including modelling, metadata, security, reference data such as product codes and client categories, and master data such as clients, vendors, materials, and employees.
- Data flow mapping – Define and document all data flows within the business, i.e., which parts of the organization generate data, which require data to function, how data flows are managed, and how data changes in transition.
- People management – Plan and manage performance, skills development, employment equity, talent, and culture of team to improve innovation, achieve efficiencies and increase competencies.
