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Shanghai ShiShanghai
Information Systems
Full - Time
08-Apr-2021

Preferred profile/ skills:

  • 6+ years of experience in data management, data quality, data modeling or similar roles within a multinational organization
  • Mastery of data modeling, data governance, data cataloguing tools (Erwin, Visio, Informatica/ Axon, Collibra, Alation etc.) and techniques (ER modeling, Kimball Modeling, Data Vault etc.)
  • Strong technical understanding of Data & Analytics concepts is mandatory (cloud-based data warehouses and marts, reporting and visualizations)

§  Ability to write advanced SQL is mandatory

  • agile methodology as a discipline
  • Pro-active, self-motivated & problem-solving attitude
  • Strong communication and organizational capabilities; and ability to work in a matrix/ multidisciplinary teams
  • Fluency in English

§  Google Cloud Platform Professional Data Engineering certification will be a big plus

§  Python or R skills will be a plus

Job objectives:

§  Work with data governance teams within business to clearly understand the taxonomies, enterprise domain data models, data families/ sub-families business objects and attributes

§  Work with project managers, solution architects within IT teams to understand data needs of a project and design, propose best-fit-for-purpose data models in compliance to enterprise domain data models. Establish and document localizations necessary to the enterprise domain data models, communicate the planned localizations to IT and business teams

Job description:


§  Work with project teams to understand data requirements translate into the enterprise data model. Ensure compliance and reusability of data model; and the model evolves correctly

  • Act as ‘Owner’ of the conceptual, logical, and physical data models to support data analysis, business intelligence and artificial intelligence/ machine learning systems
  • Act as the ‘Conduit’ between data engineers, ML engineers and data analysts to provide a model best-fit for data pipelines, analysis, and AI/ ML
  • Define and manage standards, guidelines, and processes to ensure data quality
  • Ensure technology solutions are in alignment with data architecture principles and target state
  • Oversee end-to-end data life cycle management activities
  • Establish guidelines and lead transformation towards next-gen semantic modeling using tools such as LookML, Dataform, DBT etc.
  • Evaluate and recommend emerging technologies for data management and data governance (catalog, quality, lineage, metadata management and master data management)

§  Be accountable for the data quality and system performance

§  Provide continuous improvement and optimization suggestions on data models

§  Work with internal and external parties on facilitating and delivery of Data & Analytics initiatives within APMENA Region