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Collibra Data Modeler

  • Location:

    Hong Kong

  • Sector:


  • Job type:


  • Salary:


  • Contact:

    Preksha Tripathi

  • Contact email:

  • Job ref:


  • Published:

    18 giorni fa

  • Expiry date:


  • Startdate:


Our client is seeking a Collibra Data Modeler for their new headcount hiring in Hong Kong office.


* Work on the development of conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL).
* Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices.
* Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, and machine learning).
* Knowledge of data modelling and Metadata technologies and methods of storing reference data and definitions
* Experience in linking conceptual, logical, and physical models to provide a tangible value to the business
* Maintain strict governance and standards on the usage of transaction data and models
* Work with business stakeholders and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models
* Define and govern data modelling and design standards, tools, best practices, and related development for enterprise data models.
* Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.
* Hands-on modelling, design, configuration, installation, performance tuning, and sandbox POC.

* Experience in Collibra data modelling and metadata tools
* Expertise in data modelling principles/methods including conceptual, logical & physical Data Models
* 5+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
* Knowledge of more than one financial asset class - systems, tools, processes
* Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-centre contexts required

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