Data Modeler

iVEGA Global; Sydney; On-site; AUD 120,000 - 180,000; Full time

Job summary

iVEGA Global is seeking an experienced Data Modeler to translate complex business requirements into scalable data models for enterprise data platforms, data warehouses, and analytics solutions. The role requires hands-on expertise in Erwin Data Modeler, Azure data platforms, PySpark, and SQL, with strong collaboration across business and technical teams.

The ideal candidate independently analyzes source data, defines scalable target models, documents transformation rules, and explains modelling

Qualifications

• Hands-on in Erwin Data Modeler and enterprise data modelling.
• Experience with Azure data platforms, PySpark, and advanced SQL required.

Responsibilities

• Translate complex business requirements into scalable conceptual, logical, and physical data models for enterprise data platforms and analytics.
• Collaborate with stakeholders, architects, engineers, governance teams, and downstream consumers to deliver standardized, reusable data structures.

Skills

Erwin Data Modeler

Azure data platforms

PySpark

Advanced SQL

Enterprise data modelling

Job description

• We are seeking an experienced Data Modeler with strong hands-on expertise in Erwin Data Modeler, Azure data technologies, PySpark, and SQL.
• The candidate will translate complex business requirements into scalable conceptual, logical, and physical data models for enterprise data platforms, data warehouses, lakehouses, analytics, and reporting solutions.
• The role requires close collaboration with business stakeholders, data architects, data engineers, analysts, governance teams, and downstream consumers to deliver standardized, reusable, secure, and high-performing data structures.

Mandatory Skill Combination

• The candidate must be hands-on in Erwin Data Modeler, enterprise data modelling, Azure data platforms, PySpark, and advanced SQL.
• The role requires the ability to independently analyse source data, define scalable target models, document transformation rules, validate implementations, and explain modelling decisions to both technical and business stakeholders.