Data Architect

About the role

We are looking for a Senior Data Architect - Core Data Platform & Data Science Enablement to join our team in Melbourne, Australia.

This is a high-impact role where you will help shape and evolve enterprise-scale data platforms that support advanced analytics, machine learning, optimisation, and data science initiatives. You will work closely with Data Scientists, Engineers, and business stakeholders to design scalable, future-ready architectures that enable a broad range of analytical and AI-driven use cases.

Key responsibilities

• Designing and architecting scalable, enterprise grade data platforms supporting analytics, reporting, machine learning, and data science workloads
• Leading the evolution of core data platforms to support current and future data science and AI initiatives
• Defining enterprise data architecture patterns, standards, and governance frameworks
• Collaborating with Data Scientists, Engineers, and business stakeholders to translate business requirements into robust technical solutions
• Designing and optimising enterprise data models within Snowflake environments
• Supporting the integration, migration, and consolidation of data assets into Enterprise Data Platforms (EDP)
• Establishing best practices across data modelling, governance, integration, and lifecycle management
• Supporting optimisation and measurement model use cases across analytics and data science domains
• Providing architectural leadership across modern cloud data ecosystems

About you

To be successful in this role, you'll need:

• Proven experience as a Data Architect delivering modern enterprise data platforms
• Strong experience with Snowflake
• Experience designing cloud based solutions on Azure and/or AWS
• Strong data modelling expertise, including dimensional modelling methodologies
• Experience with ERwin or similar data modelling tools
• Deep understanding of Kimball modelling principles and data warehousing concepts
• Experience in architecting platforms that support analytics, machine learning, and data science workloads
• Strong stakeholder engagement skills with the ability to communicate effectively across technical and business audiences
• Experience designing scalable, secure, and governed data platforms

You'll be at an advantage if you also have:

• A Data Science background
• Experience supporting optimisation, predictive analytics, and measurement modelling initiatives
• Knowledge of Data Vault methodologies
• Experience with Databricks and dbt (preferred)
• Knowledge of data quality, observability, monitoring, and governance frameworks
• Exposure to AI and Agentic AI initiatives

Core Technologies

• Snowflake
• Azure (preferred) or AWS
• dbt
• Databricks
• ERwin (or equivalent data modelling tools)