BI Specialist - Nedbank

Job Purpose

To work on multiple complex projects as a Data Modeler to design and maintain optimal data models/structures that enable data to be persisted and/or to enable the flow of data between providers and consumers in a structured, consistent manner.  Designing and maintaining structures that meet both the business and architectural objectives of the organization at an enterprise and/or system/application level, in order to maximize and unlock the value of data. 

Through breadth of experience gained, grow and mentor junior data modelers, review the work of other data modelers and contribute to the overall data modelling practice as a key contributing member of the CoE. Where required, lead a team of data modelers.

Job 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 Nedbank 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 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.

• When required, lead a team of data modelers, and manage day-to-day activities, allocation and growth and development
• Provide a comprehensive governance framework by working in the Data Modelling CoE and contributing towards defining the governance framework, data modelling standards and principles, guidelines, training content and delivery of training.
• Ensure consistency and re-use of data models by acting as a primary advocate of date modelling activities and methodologies and by driving the adoption of enterprise data modelling across the bank.
• Drive implementation of opportunities to improve or enhance processes.
• 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 strategic direction and maturing of the data modelling practice.
• Advise stakeholders and other staff on application of data modelling practices through consultation.
• Perform Data Life Cycle Checklist reviews for SME and Innovation projects.
• Provide Overall Data Management Guidance and alignment to Nedbank's Data Management framework and standards.
• Drive opportunities to improve business processes, models, and systems though agile thinking.
• Support the achievement of the business strategy, objectives, and values.                                
• Contribute to the Nedbank Culture building initiatives (e.g. staff surveys etc.).
• Participate and support corporate responsibility initiatives for the achievement of business strategy.

People Specification

Essential Qualifications - NQF Level

• Advanced Diplomas/National 1st Degrees

Preferred Qualification

• Bachelor of Commerce , Bachelor of Science: Information Systems / Computer Science

Essential Certifications

• The Data Management Association International (DAMA), TOGAF

Preferred Certifications

Minimum Experience Level

• 7 - 10 years

Technical / Professional Knowledge

• Data Modelling
• Data analysis
• Data Modeling Tools and Industry Reference Models
• Data and business requirements gathering
• Data Architecture
• Data Warehousing and Data Integration
• Meta data Management
• Master and Reference Data Management
• Agile and SDLC
• Data Quality and Data Governance

Behavioural Competencies

• Work Standards
• Hyper-Collaboration
• Decision Making
• Building Trusting Relationships
• Technical/Professional Knowledge and Skills
• Coaching