Vice President - Data Modeler - Retail Banking

- Excellent spoken and written communication skills. A strong ability to communicate virtually e.g. conference calls and video conferencing.

- Min. 12+ Year of relevant experience. Bachelor's or Master's degree from reputed university with specialization in data/technology.

- Strong background working with large-scale data, data management, data quality, and data resiliency domains

- Demonstrable knowledge of Data Management tools and techniques

- Good working knowledge of relevant tools e.g. Visual Paradigm, IBM Infosphere Data Architect or CA Erwin Data Modeller

- Experience of eliciting, documenting and verifying requirements for the use of data across the organisation (Global Businesses and Global Functions) as appropriate to project scope

- Experience of working within a large, complex and geographically dispersed projects (including across time zones)

- Enthusiasm for proactively seeking, exploring, and developing use cases for new data and/or tools/wider industry trends

- Experience working across multiple geographical regions desirable

- Proven ability to work in a matrix multi-national operating structure

- Proven ability to work with senior stakeholders and business sponsors

- Experience of Financial Services and specifically within data domains / functions (e.g. Data Management, Data Architecture, Data Governance)

- Previous experience as a data analyst, solutions analyst or architect including delivery of data artefacts e.g. data models, data flow diagrams & metadata would be beneficial

- Global systems that create data, such as core banking platforms.

- Data aggregation platforms, such as data warehouses and big data platforms across a range of enterprise, private and public cloud enclaves.

- Data consumption platforms that ingest, process, store or transform and distribute data updates or outputs, including systems of insight (e.g. visualisation tooling) that generate analytics, MI or other operational reporting.

- Those systems which supply data to external parties

- Data integration tools or services at a physical or logical level.

- Data models and associated domain nomenclature consistent with standard and policy

- Data patterns for all of the above.

- Knowledge of cloud providers (GCP preferred), what technologies they provide, and the use cases they serve.

- Experience of Waterfall, DevOps and agile ways of working and how architectural data risks can be effectively governed.