Data Modeller
ARCS
Johannesburg, South Africa
3d ago
source : Job Placements

Experience and Qualifications

  • Minimum Qualification - Relevant BSc or BCom degree
  • Experience - 6 to 8 years related experience
  • Additional information and responsibilities
  • Additional Requirements

    Data modeller should have excellent understanding of business as well as technical skills to translate business requirements into the Enterprise data model.

    This role works closely with the enterprise solution architects, lead information architects and DMDA members, and ingestion and consumption engineers to ensure that the physicalisation of the data model follows the FSR standards.

    This role will coordinate the extensions to the FDM within the functional / pillar areas - Ability to create data structures that enable data to be persisted in a way that enables value of data to be unlocked - Ensure that all data modelling activities, deliverables and artefacts are aligned to the development methodology and data modelling standards and principles - Relational and Dimensional Modelling proficiency - Data Profiling of source data to determine data quality issues and relationships in the data - Understanding and experience in logical and physical modelling - Ability to compile Source to Target Mappings with appropriate transformation rules Some Technologies / Language / required : SQL Database Technologies, Erwin Modeler toolset, TeraData DBMS

    Responsibilities

  • Continuously assess own performance, seek timely and clear feedback and request training where appropriate
  • Perform reverse engineering of physical data models from databases and SQL scripts
  • Manage cost related to income to increase profitability and efficiencies for the business
  • Develop policies and procedures related to development and support of new and ongoing systems to ensure the integrity of data
  • Develop and maintain the Business Matrix
  • Delivers internal and external customer service excellence through adherence to quality service standards for data management
  • Create logical and physical data models using best practices to ensure high data quality and reduced redundancy
  • Coordinate data models, dictionaries, and other database documentation across multiple applications
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