Data Engineer

Reporting to: Data Platform Manager

The Data Engineer is responsible for developing, maintaining, and enhancing the organisation's enterprise data platform, data pipelines, integrations, and analytical data assets.

Working closely with the Data Platform Manager, this role delivers scalable and reliable data solutions that support reporting, analytics, customer insights, operational excellence, and business decision-making across the organisation.

The Data Engineer will play a critical hands-on role in building and optimising data products, integrating enterprise systems, improving data quality, and enabling trusted self-service reporting capabilities. The position will collaborate with stakeholders across technology, marketing, commercial, membership, finance, racing, events, and operational teams to ensure data is accessible, reliable, and aligned with business priorities.

Stakeholders

Internal: Data Platform Manager, Head of Technology, Technology Team, Executive Leadership Team, Department Heads & Managers and the wider VRC Team.

External: Suppliers, Vendors, Stakeholders, Partners, Sponsors, Members and Guests, and the wider industry networks and associations.

Focus

Data Engineering & Platform Delivery

- Design, develop, maintain, and optimise data pipelines supporting operational, analytical, and reporting workloads.
- Build and maintain integrations between key business systems including CRM, ticketing, membership, finance, marketing, POS, racing and operational platforms.
- Develop and maintain ETL/ELT processes within Microsoft Fabric and associated data platforms.
- Troubleshoot and resolve data pipeline, integration,



and platform performance issues.
- Support the implementation of current data capabilities and platform enhancements.

Data Modelling & Analytics Enablement

- Develop and maintain curated data models, semantic layers, and analytical datasets.
- Contribute to the design and optimisation of enterprise reporting structures and Power BI semantic models.
- Prepare and transform data to support reporting, forecasting, analytics, and business intelligence initiatives.
- Enable self-service reporting through well-structured and trusted data assets.
- Work with analysts and business stakeholders to understand reporting and data requirements.

Data Quality & Governance

- Implement and monitor data quality controls, validation processes, and reconciliation frameworks.
- Support data governance initiatives through documentation, metadata management, and adherence to data standards.
- Maintain data lineage and documentation for key data assets and integrations.
- Assist in identifying and resolving data quality issues across enterprise systems.
- Ensure data handling practices comply with organisational security, privacy, and compliance requirements.

Platform Operations & Support





- Monitor and maintain day-to-day operation of data pipelines and platform services.
- Ensure high availability, reliability, and performance of data solutions.
- Support root cause analysis and remediation of platform incidents.
- Assist with release management, testing, and deployment activities.
- Contribute to continuous improvement initiatives that enhance platform stability and efficiency.

Business Engagement & Continuous Improvement

- Collaborate with business users to understand operational and reporting needs.

- Translate business requirements into scalable technical solutions.

- Contribute ideas that improve data accessibility, usability, and trust.
- Support the adoption of data-driven decision making across the organisation.
- Identify opportunities to automate manual processes and improve operational efficiency.

Success Measures (KPIs)

- Platform Reliability: High availability and stability of data pipelines and integrations.
- Delivery Performance: Timely completion of backlog items, project deliverables, and platform enhancements.
- Data Quality: Consistent improvement in data accuracy, completeness, and integrity.
- Operational Efficiency: Reduction in recurring data issues, manual effort, and platform support incidents.
- Stakeholder Satisfaction: Positive feedback regarding responsiveness, quality of delivery, and technical support.
- Documentation & Standards: High levels of compliance with data engineering and governance standards.
- Continuous Improvement: Ongoing identification and implementation of platform and process improvements.

Core Capabilities

- Data Engineer

📌 Data Engineer (Melbourne)
🏢 Victoria Racing Club
📍 Melbourne