Data Modeler Lead
3 days ago
The Teradata Data Modeler Lead is a consulting delivery role as part of Teradata DWH projects delivery engagements.
Teradata Data Modeler together with Business Analysts contributes in the delivery of the business analysis and data design workstream for Teradata services delivery and must have a deep understanding of the fine points of the data arena: data warehousing, big data, data usage, tools, and analytics, in order to extract the correct requirements from our clients and correctly design solution from data perspective.
**Responsibilities and duties**:
As a Data Modeler, you are responsible for the business analysis and data design workstream using Teradata methodologies and processes, including activities such as but not limited to:
Data design - data modelling, data flow, data transformations
Workstream scoping, planning and execution
Requirements elicitation, definition and management (functional, non-functional) and associated documentation lifecycles
Communications and stakeholder management
Prototyping and UAT.
Mapping business rules to logical model
Perform recommendation for transfer of logical model to Physical model
**Basic requirements**:
8+ years’ experience in similar role
Degrees Computer Science, Engineering or other related areas is desirable
Knowledge/Experience in Data warehousing, big data, data modelling and data analysis
Industry experience from one or more core industries (e.g. finance, insurance, Government, Taxation, telco) preferable Government.
Familiarity with both traditional and agile IT project delivery and development cycles
Requirements documentation and information gathering techniques
Excellent written and oral English and Arabic with experience preparing and managing documentation of senior-level client deliverables in both languages.
Excellent communication and presentation skills
Detail focussed, resourceful, decisive, composed, problem-solver, flexible and adaptable
Working effectively in multi-disciplinary and cross-organizational teams
**Technical requirements**:
Skills, Knowledge & Experience (M = Must have; S = Should have)
Data architecture and data modelling (M)
Data analysis (M)
Advanced SQL (S)
Data integration principles (M)
Data integration software (S)
**BI tools**: specification, development, and use (e.g. Tableau/QlikView/BO) (S)
**Requirements management tools**: e.g. JIRA, Jama, Trello (S)
DataOps and DevOps tools and principles (like git, Jenkins, code automation tools) (S)
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