Data Domain Architect, Sparx, Modelling

4 weeks ago


London, United Kingdom Experis - ManpowerGroup Full time

6 Months Initial Duration

Project likely 24-36 months in total duration

100% remote


My client a leading solutions provider in the UK are seeking to recruit a Data Architect to join a team of 70 data architects, data modellers and solution architects all working on a variety of different projects at different stages of the lifecycle.


The Data Architect role is critical to ensuring the success of the digital workstream by taking a holistic view across the integration of systems to ensure clarity on how data will be used and managed, whilst ensuring that data architecture is documented and follows due process.
They will also provide practical data management expertise and data governance assurance to the Retail business and contribute to the development of the data strategy through a continuous improvement approach.


Key responsibilities.

  • Development of the business domain and project data models and integration maps. Logical Data and Physical Data Models, Data Flow Diagrams, and Source & Target mappings produced to established standards, in a timely manner to promote project needs and developmental milestones.
  • Promote Corporate Master Data Management development through data definition, identification, and classification (data types and sensitivity including Data Protection Act requirements). Data is uniformly identified and has accepted data definitions and classifications to enable data governance requirements to be clearly defined, documented, and understood by responsible business Data Governance roles.
  • Defining the Data Governance approach for managing data changes for the lifecycle of the data eg: maintenance, quality monitoring, retention, etc) and ensuring compliance with external data governance legislation (eg: GDPR) is designed.
  • A consolidated set of collateral of metadata maintained as part of change processes (eg: Delivery framework Data Platform, and Integration Wikis).
  • Support data quality improvement initiatives by developing data quality assessment standards. Definition of data quality assessment metrics and mechanisms to implement agreed with the Data Owners.
  • Knowledge of Sparx and Erwin desirable.
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