Lead a team of Data Modellers
To design and maintain data models / structures at both enterprise and system / application level. To persist data in an efficient and structured way to enable the value of the date to be unlocked.
To create appropriate data and class structures that enable the flow of data between providers and consumers.
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 Bank 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.
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.
Assists to provide a comprehensive governed framework by working with the data modelling CoE and contributing towards defining the data modelling standards.
Advise stakeholders and other staff on application of data modelling practices through consultation.
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 date modelling across the bank.
Ensure improved performance by providing feedback on improvements to the data modelling framework.
Perform review on work performed by team members as well as review and govern work performed by other modelling teams
Identify opportunities to improve or enhance processes.
Provide Overall Data Management Guidance and alignment to Bank's Data Management framework and standards
Seek opportunities to improve business processes, models and systems though agile thinking.
Support the achievement of the business strategy, objectives and values
Contribute to the Bank Culture building initiatives (e.g. staff surveys etc.).
Participate and support corporate responsibility initiatives for the achievement of business strategy
Ensure consistent, quality delivery of data models and data modelling artefacts by the team and / or self
Lead the team of data modellers within the data warehouse squad in the delivery of sprint goals
Ensure resources are skilled an able to perform work and grow and develop their skills through coaching
Ensure resource allocations are managed
Monitor and Report on progress and alignment to priorities
Bachelor of Science : Information Systems / Computer Science
The Data Management Association International (DAMA), TOGAF
Type of Exposure
Achieved transformation and innovation results
Designed Workforce Planning Solutions
Developed and Implemented Communications Strategy
Manage internal process
Critical Required Skillls
Data analysis and inference
Data Warehouse Layers
Data Warehousing Overview and Architecture
Database Model Concepts
Data and business requirements gathering
Data Modelling Tools
Industry Model Understanding
Pattern Recognition, conceptual and abstract thinking
Minimum Experience Level
5 - 8 Years as a Data Modeller
Able to demonstrate practical experience in relational and dimensional modelling techniques as well as leading teams of data modellers
Has demonstratable experience in developing custom data models as well as data modelling utilising Industry data models such as IFW BFMDW
Experience in model management
Experience in compiling and monitoring standards and developing / maturing a data modelling practice
OO modelling experience also an advantage
Exprience using Infosphere Data Architect or any other Data Modelling Tool
Firm 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
Administrative procedures and systems
Business terms and definitions
Governance, Risk and Controls
Relevant regulatory knowledge
Relevant software and systems knowledge
Business writing skills
Cluster Specific Operational Knowledge