Data Modeler: Build Scalable, Cloud Data Foundations

Cognizant; City of Melbourne; On-site; AUD 110,000 - 150,000; Full time

Job summary

Cognizant in Melbourne is seeking an experienced Data Modeler to design and develop scalable data models across modern data platforms. You will work with business stakeholders, data architects, and data engineering teams to build data foundations, analytical data marts, and business-ready data products.

The ideal candidate has strong expertise in data warehousing, dimensional modeling (Kimball), data governance, and cloud-based analytics platforms, with a track record of delivering performant

Qualifications

• Experience in logical/physical data modeling and dimensional modeling.
• Ability to design fact and dimension tables for BI.
• Proficiency with cloud data platforms and ETL/ELT concepts.
• Knowledge of data lineage, metadata, and data quality frameworks.

Responsibilities

• Design and maintain logical and physical data models.
• Define fact, dimension, and aggregate tables for reporting.
• Develop scalable data structures for BI and analytics.
• Create source-to-target mapping documentation.
• Define data relationships and transformation logic.
• Design data models across Raw Data Layer, Curated Data Layer and Business/Semantic Layer.
• Build and optimize dimensional models using Kimball methodology.
• Ensure consistency, reusability, and performance of analytical datasets.
• Collaborate with governance teams to ensure compliance with data policies.
• Translate business requirements into scalable data solutions.
• Provide guidance to data engineers during implementation.

Skills

Data Modeling

Dimensional Modeling

Kimball Methodology

Star Schema

Snowflake Schema

Cloud Platforms

Data Governance

Job description

Cognizant in Melbourne is seeking an experienced Data Modeler to design and develop scalable data models across modern data platforms. You will work with business stakeholders, data architects, and data engineering teams to build data foundations, analytical data marts, and business-ready data products.

The ideal candidate has strong expertise in data warehousing, dimensional modeling (Kimball), data governance, and cloud-based analytics platforms, with a track record of delivering performant