Contribute in overall modeling standards, guidelines, best practices and approved modeling techniques and approaches.
Contribute in governing the creation of all physical and logical data models in the organization.
Participate in due diligence of new software purchases by reviewing all proposed data models contained in packaged or commercially available applications.
Serve on data integration, business intelligence and content management competency panels or teams.
Participate in all data integration and Enterprise Information Management (EIM) programs and projects — both enterprise and point-to-point efforts — by rationalizing data processing for reusable module development.
Work jointly with the data services administrator in developing the data objects and data models to support data services under a service-oriented architecture approach.
Govern the data administration team (modeling, metadata managers and end-user query optimization).
Liaise with the data modeling team, data warehouse team and the application owners in understanding the data interface requirements and help the project team developers to resolve issues related with data requirements. Ensure, gatekeeper functions are effectively defined and managed to reduce data redundancy and increase accuracy.
Contribute in selection of data management tools, and the development of standards, usage guidelines and procedures for those tools.
Document the existing data architecture in a prioritized manner in order to maintain an accurate ‘as is’ view of the current data environment and define the “to be” view.
Document the Data Flows / lineage visualizing the "as-is" data movement across key components of the Data landscape and define the "to-be" views.
Work & liaise with various technology and business stakeholders in resolving and escalating issues related with the data solutions and seek their concurrence and approval as per the established process during the SDLC until the solution is deployed.
Provide feedback and improvements over the standards, methodologies, processes and best practices to the enterprise architecture team to review and update enterprise architecture standards both at the group and country level.
Feedback and improve towards corporate metadata management facility.
Work with the Data Quality / Governance teams in understanding areas where data architecture enhancement will assist the overall quality of the Group’s data.
Educate senior business representatives in best practices for data quality and to work with them to identify realistic goals and data initiatives.
