Zanaco is seeking an experienced Enterprise Data Architect to lead and oversee our organisation’s comprehensive data architecture strategy. In this role, you will be responsible for planning, documenting, and implementing a cutting-edge data architecture that aligns with business objectives. You will define a clear, sustainable strategy while designing and executing target architectures. Additionally, you will develop tailored data solutions for specific business needs, including data warehouses, data marts, and data lakes, driving innovation and efficiency across the organisation.
Design and implement data architecture(s) supporting the storage, processing, and analysis of large volumes of data.
Job responsibilities:
Customer:
- Develop a service culture which builds rewarding relationships, proposes innovations, and allows others to provide exceptional client service
Cultivate and manage objective working relationships with a variety of stakeholders, including end-users, SME’s, project managers and senior staff members to ensure implementation of a target data architecture.
Business Growth:
- Plan, document, and implement a new data architecture; define a clear and sustainable data architecture strategy; and design-and-implement the target architecture(s)
- Identify business opportunities or create new business concepts and development approaches to support business growth through data tools and models.
- Analyse and develop a data architecture fit for data analytics, Artificial Intelligence (AI), and Machine Learning (ML) based on an environmental analysis that incorporates all internal and external benchmarking data for future solutions.
- Facilitate the conversion of knowledge and ideas into new improved products for the data environment.
Leadership and staff development.
- Establish, align, and manage target and budget goals whilst ensuring effective control of costs to increase cost efficiency.
- Plan and manage performance, skills development, employment equity, talent, and culture of team in order to improve innovation, achieve efficiencies and increase competencies.
- Manage own development to increase own competencies.
Process:
- Using data modelling tools such as ER/Studio to visualize and design data architecture
- Documenting data pipeline procedures or queries for metadata and reference data cases.
- Monitoring changes in merging technologies, legislation, regulations, initiatives, and relevant industry practices. Ensure compliance with audit requirements.
- Controlling the management of agreed data architecture projects to ensure successful implementation within agreed timelines and ensure effectiveness of projects by investigating the integrated nature of the project, requirements must be distributed to all affected Business units in order that they prioritise the project.
- Supporting best practise and innovation in the operational model through critical assessment of its workings and challenges to its design assumptions so that data and subsequently analytics can make a relevant difference.
Key outputs:
- Service Culture
- Process Improvements and New Innovations
- Cost Containment
- Strategic Planning
- Project Implementation
- Data Flow Mapping
- People Management
- Personal Development
