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Head, Data Services Job at Commercial Bank International Dubai United Arab Emirates

 CBI is looking to hire a Head, Data Services

  • To own the strategy and delivery of data, data architecture, and supporting capabilities across the bank
  • To define and deliver the bank’s cloud-data and big-data capabilities, and predictive analytics within the organization
  • The role is responsible to develop and implement a Data framework through the centralized data warehouse to support the overall MIS and analytic requirements of the business.
  • To lead, implement and manage a centralized bank data model for the bank business and operational teams which factors the required business KPIs and regulatory reporting requirements. 

Ideal Profile

Minimum Qualifications:

  • Bachelors or Master Degree in computers or information systems or related adequate experience
  • Preferred: Degree or Post Graduate Degree in related field of study (in or involving Data Science, Statistics)
  • Specialist in Data Science

Professional / Technical Qualifications / Diplomas:

  • Qualifications and or trainings around Data Analysis and Visualization using technologies / tools such as SQL, DB2, Qlick Sense, Power BI, SSRS, Business objects, Crystal reports, Hadoop, MS Access, VBA and/or similar

Minimum Experience:

  • Experience supporting Big Data Projects
  • Banking, investment or financial industry experience
  • Familiarity with UAE banking regulations and banking systems
  • Further AML, CTF and/or other Compliance experience or qualifications are preferred
  • A minimum 5 years’ experience managing a similar department or function

Job-Specific Knowledge & Skills:

  • Proven working experience in Data Modelling, analysis and reporting
  • Experience of cloud and big-data platforms – Azure, AWS, etc.
  • Strong knowledge of and experience with reporting packages, databases, programming languages (like SQL, DB2, Qlick Sense, Power BI, SSRS, Business objects, Crystal reports, Hadoop, MS Access, VBA and/or similar)

Duties and Responsibilities:

  • To develop and implement a central Bank Data model across all business lines and operational / support functions
  • To maintain the data model in a centralized data warehouse (MS SQL 2017) which will support the overall reporting and MIS requirements of the business.
  • To build & deliver capabilities that would enable business to perform self-service around reporting, analytics and dashboard
  • To design and deliver predictive analytics solutions
  • To design and deliver capabilities for cloud-data and big-data across the bank
  • To ensure that the data model factors all the required business KPIs (loans, cards, Islamic and wholesale banking products) and regulatory reporting requirements which will eliminate any calculations or logic derivations in the reporting / visualization platforms
  • To own and be responsible for managing / supporting the overlaying reporting / visualization tools (such as Qlik, business objects, crystal reports, SSRS, power BI etc.) through best practice deployment, management and maintenance processes.
  • To continuously enhance / maintain / adapt the data model with the changing business and operational requirements as well as with the introduction of new systems and processes.
  • To be responsible for the application stacks (Application and Infrastructure) around data warehouse, reporting and the required ETL / integration tools, in terms of software versions, optimization of queries as well as relevant EOD batch processes.
  • To build & deliver capabilities that would enable business to perform self-service around reporting, analytics and dashboard
  • To lead and direct the development and implementation of effective IT processes, services and controls around Data warehouse that help ensure the realization of the IT strategy, and enable business to perform self-service in terms of developing and maintaining their own reports / dashboards and perform business analytics
  • To participate in project / change discussions and provide inputs on how the centralized data model can be used to optimize processes and decision
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