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Open nowFirst seen 2 days ago

Data Modeller

Boardroom Appointments3,354 open roles

Where
Johannesburg, GP, South Africa
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Your applicationOpen nowData ModellerBoardroom Appointments · Johannesburg, GP, South Africa
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Share of postings closed within
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  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: first seen 2 days ago

The posting

Minimum requirements:

  • Minimum Experience Level
  • 3-5 years and/or relevant industry experience as well as experience in the Data Modelling discipline
  • Advanced Diplomas/National 1st Degrees
  • Bachelor of Commerce , Bachelor of Science: Information Systems / Computer Science (preferred)
  • TOGAF
  • DAMA certified data management professional (CDMP) or similar data management certification
  • 3yrs IT related experience with 2yrs+ in a Data Modelling role
  • Able to demonstrate practical experience in relational and dimensional modelling techniques, OO modelling experience also an advantage
  • Exprience using Infosphere Data Architect or any other Data Modelling Tool
  • Experience with industry models such as IFW BFMDW
  • Broad understanding of Data Management (DMBOK), systems development lifecycle methodologies and IT Architecture
  • Relevant regulatory knowledge, and understanding of banking and financial services
  • Experience in NOSql and other forms of database modelling advantageous

Technical / Professional Knowledge:

  • Data analysis
  • Data Analysis and Interpretation
  • Data Warehousing
  • Data and Business analysis
  • Data base Administration (DBA) Principles and Admin Concepts
  • Data base administration
  • Data modelling tool
  • Database Knowledge
  • SQL
  • Problem solving skills

Responsibilities:

  • Design data models that meet the business requirements and align to the agreed architecture framework.
  • Ensure data modelling deliverables are delivered according to project plan and budget to meet commitment to stakeholders.
  • Ensure all data modelling activities and deliverables are aligned to the development methodology and to the data modelling principles and standards
  • Apply the company approved tooling to create the data modelling deliverables.
  • Adopt the Enterprise Data Model (which is based on the IFW) as a standard for data model designs to leverage best practice and fast track data modelling efforts.
  • Translate business requirements into data requirements.
  • Analyse and profile the source data to understand data quality issues, relationships, patterns and rules in the data.
  • Structure data requirements into logical data constructs based on the Enterprise Data Model, including ERD models, dimensional models and UML class models to ensure optimal implementation.
  • Compile Source to Target Mapping Specifications including the appropriate Transformation Rules
  • Identifying definitive or authoritative source of data; analysing source data; and identifying gaps to target structures
  • Enable physical implementation of the data structure by generating the first cut physical data model from the logical data model.
  • Facilitate dataflow understanding by collating dataflow diagrams outlining the flow of data across systems and interfaces.
  • Reduce non value adding work by identifying opportunity for re-use of the Enterprise Data Model
  • Maintain up to date knowledge of latest developments in the Data Modelling domain, including reading; continuous professional development courses; seminars and conferences.
  • Contribute to the creation of a comprehensive governed framework by working with the data modelling CoE and contributing towards defining the data modelling standards.
  • Advise stakeholders on application of data modelling practices through consultation.
  • Perform peer review on work performed by other team members
  • Identify opportunities to improve or enhance processes
  • Provide Overall Data Management Guidance and alignment to the company's Data Management framework and standards
  • Seek opportunities to improve business processes, models and systems through agile thinking.
  • Support the achievement of the business strategy, objectives and values
  • Contribute to the company's Data Culture building initiatives (e.g. staff surveys etc.)
  • Participate and support corporate responsibility initiatives for the achievement of business strategy
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