Business Analyst- Data Modelling & Architecture
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Key skills for this role
About the Role
We are looking for a detail-oriented and analytical Business Analyst with strong expertise in data modelling tools such as Erwin, ER Studio, and equivalent platforms.
Key Skills for This Role
Full Job Posting
Overview
We are looking for a detail-oriented and analytical Business Analyst with strong expertise in data modelling tools such as Erwin, ER Studio, and equivalent platforms.
The ideal candidate will bridge business requirements and technical solutions by translating complex data needs into structured models, ensuring data accuracy, consistency, and quality across systems.
Key Responsibilities
- Gather, analyze, and document business requirements from stakeholders.
- Translate business needs into logical and physical data models.
- Design and maintain data models using Erwin, ER Studio, or similar tools.
- Collaborate with data architects, developers, and business teams to ensure alignment.
- Perform data analysis, data mapping, and data lineage documentation.
- Ensure data integrity, normalization, and standardization across systems.
- Support data governance and data quality initiatives.
- Create and maintain data dictionaries, ER diagrams, and metadata repositories.
- Identify process improvement opportunities and recommend data-driven solutions.
- Assist in UAT (User Acceptance Testing) and validate data-related requirements.
- Provide insights through reporting and data analysis to support decision-making.
Required Skills & Qualifications
- Bachelor’s degree in information technology, Computer Science, Business Administration, or a related field.
- 3–8 years of experience as a Business Analyst, preferably in data-centric roles.
• Erwin Data Modeler
- ER Studio
- Other data modelling tools (e.g., PowerDesigner, Oracle SQL Developer Data Modeler)
Strong Understanding Of
- Data Modelling (conceptual, logical, physical)
- Database design principles
- ER diagrams and normalization techniques
- Proficiency in SQL for data analysis.
- Experience in data mapping, ETL processes, and metadata management.
- Familiarity with data governance frameworks and data quality tools.
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