Job title : Data Modeller-1
Job Location : Gauteng, Johannesburg
Deadline : December 01, 2025
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Are you someone who can
Execute on data modelling standards, principles, frameworks and toolsCoordinate and prioritise the data modelling work within the Business areaInvolved in the entire data modelling lifecycle i.e. Logical to Implemented Physical Model and Semantic ModelUnderstand 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 stakeholdersProvide input into key metrics related to measuring the progress with respect to data modellingOptimise and update logical and physical data models to support new and existing projects for Business areaEnsure that the source to target mapping is done in accordance to the requirementMaintain all extract, transform, load (ETL) and business rules within the data modelMaintain all model related metadataRecommend opportunities for reuse of data models in new environmentsReview modifications to existing data modeling software to improve efficiency and performanceEvaluate data models and physical databases for variances and discrepanciesEnsure modelling standards and principles are always adhered toDevelop modelling standards and principles as neededYou 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 methodologyExperience working in data warehousing environment with good understanding of data ingestion, enterprise alignment (ETL) and design based on consumption requirementsKnowledge of dimensional data modelling using Kimball methodologyExperience 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
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