Supply Chain Master Data Controller - Guinness



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Guinness Supply Chain/Logistics/Warehousing Jobs in Kumasi


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GGBL operates in a growing but highly driven market where productivity and product quality are essential to business success.

The business has seen significant investment over the last few years in terms of capacity and innovation.

To support our growth and agenda the Master Data Controller will drive key Material Ledger inputs to influence accurate outputs like efficiency, inventory value, brand profitability, COGS and customs and excise payment.

Purpose of Role

Support innovation & brand change process, to craft the right data structures & manage the lifecycle of Supply Chain Master Data (Material Master & BOM).

Create an accurate Material Master Data


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Top 3-5 Accountabilities

  • To develop and deliver all project data requirements for small to large-scale brand change solutions on behalf of the project team, including Material Master Data and Bill of Material Master Data.
  • To proactively manage the product life cycle i.e. crafting, developing and amending product codes, creation of all new material and liquid specifications, and to obsolete products which have reached the end of their lifecycle.
  • To connect with the relevant other key collaborators – e.g. the identification of the component purchase price with Source COE; master data set up and amendment with GBO Data organization.
  • To drive the relevant actions based on the outputs of the monthly Data Quality KPIs, and ensure overall data quality is always at a high level.
  • Drive relevant process & data improvements to ensure efficient and effective processes & good data

Qualifications and Experience Required

  • Bachelor’s degree (Computer Science, Science, or related areas.) + 3 years experience in the brewing industry.
  • A keen eye for detail and an understanding of the importance of accurate data.
  • Ability to work quickly and accurately under pressure.
  • Strong communication and organisation skills
  • Knowledge of SAP ECC, PLM, and the relevant data objects.


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