N
Nexus Corporation
Data Analyst Data Modeler
Skills
Data EngineeringAI
15 days ago
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Important information
Contract type:
Freelance / Contract
Location:
Hong Kong
Work mode:
Onsite
Published on:
5 October 2026
What they need
Key Responsibilities
- Design implement and document data architecture artifacts and data modelling solutions
- Develop conceptual logical and physical data models using data modelling tools such as Erwin
- Build data lineage by stitching business terms in Group Data Management tools eg Collibra to logical and physical data model elements
- Provide guidance and assistance to data engineering teams regarding physical data object implementation
- Perform data discovery attribute mapping and data artifacts documentation generation eg data dictionary leveraging AI where applicable
- Provide guidance on data quality rules and facilitate data checks and profiling for Sources of Record SoRs deployment
- Support data preparation data provisioning and data self service automation initiatives
- Collaborate with business stakeholders and product owners to clarify business requirements definitions and processes and implement fit for purpose data models efficiently
- Align Application Logical Data Models ALDM with Enterprise Logical Data Models ELDM and enterprise standards
- Draft and align data standards and naming conventions for data artefacts across different data platforms
Required Skills Experience
- Experience in data modelling data architecture and data management
- Strong handson experience with data modelling tools such as Erwin
- Experience working with data governance and metadata management tools such as Collibra
- Knowledge of conceptual logical and physical data modelling principles
- Experience with data lineage data quality data profiling and data dictionary creation
- Familiarity with data engineering concepts and physical data object implementation
- Experience gathering and translating business requirements into data models and data artifacts
- Strong stakeholder management and communication skills with the ability to work closely with business users product owners and technical teams
- Experience in defining and implementing data standards naming conventions and enterprise data governance practices
- Exposure to AIenabled data discovery documentation generation and data management activities is an advantage
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