Data Modeller-1 at FNB South Africa

Are you someone who can

• Execute on data modelling standards, principles, frameworks and tools
• Coordinate and prioritise the data modelling work within the Business area
• Involved in the entire data modelling lifecycle i.e. Logical to Implemented Physical Model and Semantic Model
• Understand the reference and master data requirements and co-ordinate the use of surrogate keys and enterprise code values when building out data products with relevant stakeholders
• Provide input into key metrics related to measuring the progress with respect to data modelling
• Optimise and update logical and physical data models to support new and existing projects for Business area
• Ensure that the source to target mapping is done in accordance to the requirement
• Maintain all extract, transform, load (ETL) and business rules within the data model
• Maintain all model related metadata
• Recommend opportunities for reuse of data models in new environments
• Review modifications to existing data modeling software to improve efficiency and performance
• Evaluate data models and physical databases for variances and discrepancies
• Ensure modelling standards and principles are always adhered to
• Develop modelling standards and principles as needed

You will be an ideal candidate if you have experience in

• Knowledge of logical data modelling, and use of industry data models (e.g.IBM, Teradata, etc.).
• Understanding of the Inmon methodology
• Experience working in data warehousing environment with good understanding of data ingestion, enterprise alignment (ETL) and design based on consumption requirements
• Knowledge of dimensional data modelling using Kimball methodology
• Experience using data modelling technologies such as Erwin.
• Developing data models in a banking environment. Understanding and experience in implementing data management domains and technologies (e.g. data modelling, metadata management, data quality and profiling, information architecture, etc.).
• Experience in networking and team collaboration, communication, and presentation.

Experience

• 4-5 years experience in a data environment with hands-on relational, dimensional, and/or analytic experience (using relational database management systems (RDBMS), dimensional, NoSQL data platform technologies, and extract, transform, load (ETL) and data ingestion protocols). Experience with data warehouse, data lake, lake house and enterprise big data platforms in multi-data-center contexts required

End Date: October 31, 2025