9 months ago
23 Sep 00:00
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Reporting to the Senior Data Management and Analytics Manager, the selected candidate will be responsible for leading the Group's Data Architecture covering data models, policies and standards that govern the collection, storage, and use of data across the Bank's different business lines and platforms.
Duties and responsibilities
- Creating and maintaining detailed architecture documentation covering data/system integrations for both internal and external data sources
- Analysing and understanding business processes and how these are reflected in the underlying data
- Forming and Owning the central, multi-domain data dictionary in line with BCBS-239 requirements, and extending and maintaining the data model library including lineage
- Establishing and ensuring adoption of standard modelling and data management tools and processes
- Collaborating with other areas within Technology to ensure that the data stack is complete, operable, and meets business needs
- Contributing to the Data Strategy with a focus on reusability, rationalisation, simplification and legacy decommissioning
- Defining and measuring Key Performance Indicators (KPI's) on incoming data quality in order to facilitate improvement of upstream information
- Building out capability for data profiling and collaborating with the Data Engineering team on the evolution of the group's universal data warehouse to cater for new business lines as these are added
- Participating in the upkeep of the Technology and Data roadmaps to ensure a scalable data architecture to support business strategies
Required knowledge, skills and experience
- A minimum of 5 years' experience being an IT or Data professional and a proven track-record in the information architecture space and the establishing of standard practices and governance
- Experience building large Operational Data Sources (ODS's), Data Warehouses and Big Data platforms as well as proficiency creating logical data models, preferably within the financial industry
- Good understanding of model information structures, data gathering requirements, user needs and behaviours, organisational platforms and labelling techniques
- Experience within the Accounting or Financial industry
- Knowledge of basic banking concepts, constructs, or data categories and their relationships including trades capture or lifecycle, reference data, market data and, risk measures
- Experience using Data Modelling tools such as Erwin, ER Studio, Toad or SQL Power Architect
- Experience using cloud services such as the AWS eco-system (including S3, Redshift, and Lambda) will be considered an asset
- Previous experience in Leveraged Finance, Credit or Market Risk platforms such as Moody's Analytics will be considered an asset
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