Data Modeller

2 weeks ago

Parow, Western Cape, South Africa On Point HR & Talent Solutions Full time R200 000 - R250 000 per year

Only candidates who meets the minimum requirements will be considered

REQUIREMENTS:

5+ years of experience in data modeling, information architecture, or a related field.

Expertise in SQL, NoSQL, and data modeling tools

Relevant completed Degree

Experience working with big data platforms (e.g., GCP).

This role will be responsible for designing, structuring, and optimizing data models that enable efficient storage, retrieval, and use of data across the organization. You will collaborate with business analysts, data engineers, and stakeholders to ensure data is well-organized, accessible, and aligned with business needs.

As a Data Modeler, you will be responsible for implementing conceptual and logical data models that support cloud-native architectures.

KEY RESPONSIBILITIES:

Data Modeling and Design:

Translate business requirements into high-quality data models.

Shape how information flows and connects.

Ensure information is technically integrated and contextually aligned with business decision-making needs.

Develop and maintain enterprise reference models, taxonomies, and data designs.

Define metadata, semantic layers, and information flow standards that enhance data quality, regulatory compliance and business usability across systems.

Data Governance & Standards :

Establish data governance standards, ensuring data integrity, normalization, and consistency.

Collaborate with data governance teams to align models with enterprise standards.

Document data models, relationship, and business rules.

Collaboration & Stakeholder Engagement

Engage with business stakeholders to understand data needs and define modelling requirements.

Translate strategic information needs into actionable design artifacts; create and maintain high-quality documentation and diagrams.

Provide expertise on best practices for data modelling.

REQUIREMENTS

Knowledge of cloud-based data architectures.

Knowledge of machine learning pipelines and AI-driven data structuring.

Understanding of data visualization best practices for self-service analytics.

Strong understanding of relational databases, dimensional modeling, and data warehousing.

Knowledge of metadata management, taxonomies, and business glossaries.

Ability to translate business requirements into scalable data architectures.

Familiarity with data governance frameworks and best practices.

COMPETENCIES

Organizational sensitivity, Structuring, Listening skills, Directing, Innovating, Analyzing and forming opinions., Decisiveness

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