Data Modeller [T500-26926]

About Officeworks: Officeworks’ purpose is “we bring big ideas to life at low prices”. We are Australia’s leading omnichannel retailer of complete technology solutions, stationery, furniture, art supplies, and learning resources. We also offer services including Print & Create and Geeks2U. We begin with customers—our products and services provide solutions to our diverse range of customers across Australia, from households, students, small to large-sized businesses, governments, and schools.

About the Data and Analytics Function: By joining the Data, Analytics and AI Hub within Officeworks’ Global Capability Centre (GCC), you will play a pivotal role in enabling business growth and performance through insight, intelligence and innovation. You will support executing the strategy and accelerate the shift to a more digital and AI-native organization. You’ll help build advanced capabilities that sit at the core of how the business understands customers, informs decisions, invests wisely, and delivers measurable value. The GCC is a critical enabler of Officeworks’ purpose, by providing data-driven insights, trusted analytics, and scalable AI solutions that empower smarter, faster decision making and support sustainable success. This is a unique opportunity to join as a founding member of a newly established global hub. Early joiners will help shape how data, analytics and AI shape Officeworks, influencing future ways of working, building critical capabilities, and driving the evolution of some of Officeworks’ most important data and intelligence platforms.

These roles are best suited for people who enjoy:

• Working in data, analytics and AI disciplines, including data engineering, reporting, advanced analytics, machine learning, governance, and insights generation.
• Supporting global initiatives by building scalable, high quality data and AI products.
• Enabling business transformation through insight-led storytelling, experimentation, and continuous improvement.
• Thriving in an environment where your expertise is valued, your development is intentionally supported, and your work has a visible, meaningful impact on business outcomes.

Why this role exists: The Data Modeler provides the foundational structural design for Officeworks’ data assets, ensuring information is organized, accessible, and high-performing across enterprise platforms. By designing robust logical and physical models for Snowflake and Datasphere, this role enables the business to transition toward a self-serve analytics model and democratised data access. The role plays a critical part in the execution of the enterprise data strategy, bridging the gap between raw data ingestion and the delivery of curated, semantic layers that power advanced analytics and AI initiatives.

Where you will make a difference: In this role you will:

Data Architecture & Modelling:

• Design and maintain complex logical and physical data models for the Snowflake enterprise data platform and SAP Datasphere.
• Define and develop curated and semantic layers to ensure data is structured for optimal business consumption.
• Ensure all data models align with established canonical models and the enterprise business glossary to maintain consistency across the Technology function.

Performance & Optimization:

• Optimize data models and structures to ensure high performance, scalability, and cost-efficiency within cloud environments.
• Support data lineage and metadata integration to ensure transparency, traceability, and trust in data assets.
• Collaborate with Data Engineers and Architects to ensure physical implementation aligns with architectural intent and performance requirements.

Process Improvement & Continuous Improvement:

• Proactively identify opportunities to streamline data modelling workflows and improve the quality of the data lifecycle.
• Drive continuous improvement initiatives within the Data & AI team to enhance operational efficiency and technical documentation standards.
• Contribute to the evolution of data modelling standards and best practices at Officeworks, ensuring they remain fit-for-purpose as the AI and data landscape evolves.

Who you will be working with:

• Data Team: Collaborate with Engineers, Architects, and the Data Platform Manager to deliver integrated data solutions.
• Analytics Teams: Partner with Data Scientists and Analysts to ensure data structures support advanced analytical models.
• Business Stakeholders: Interact with functional partners to understand reporting requirements and translate them into semantic data models.
• Quality Teams: Engage with QA Associate Analysts to ensure data models meet rigorous enterprise standards and governance requirements.

What success looks like:

• Model Integrity: Data models are accurately aligned with the enterprise canonical model and business glossary.
• Platform Performance: Snowflake and Datasphere environments operate efficiently with optimized query performance and structured semantic layers.
• Operational Excellence: Consistent delivery of high-quality documentation and improved data modelling processes within the Data & Analytics hub.
• Self-Serve Enablement: Successful delivery of data assets that enable business users to perform self-serve analytics with minimal intervention.

How you will lead: Individual Contributor:

• Lives our Officeworks values and behaviours
• Proactively contributes to a safe working environment, escalates appropriately if there are unsafe conditions or inappropriate behaviour
• Operates in line with applicable Officeworks company policies and Code of Conduct
• Demonstrates a strong sense of personal accountability and curiosity to learn and develop

Qualifications and work experience: Essential:

• Education: Bachelor’s degree in Computer Science, Mathematics, or a related field.
• Experience: Minimum of 3-5+ years in Data Modelling or Data Engineering roles, with a focus on designing enterprise-scale data warehouses.
• Technical Expertise: Proven experience in logical and physical data modelling, specifically for Snowflake and SAP data environments.
• Platform Knowledge: Hands-on experience with Snowflake, GitHub, and modern data warehouse architectures (Medallion/Layered architecture).
• Adaptability: Demonstrated ability to adapt technical skills from traditional Machine Learning environments to emerging AI-driven data requirements.
• Analytical Skills: Strong ability to translate complex business requirements into scalable technical data structures.

Preferred:

• Industry Experience: Experience within a large-scale Retail or complex commercial environment is highly regarded.
• Advanced Systems: Familiarity with SAP BW migration projects or SAP Datasphere.
• Tooling: Experience with enterprise data modelling tools and metadata management platforms.