Your new role The Lead Data Architect is the Program's principal data architecture authority. The role is accountable for data architecture standards across all product and platform streams, ensuring coherence and alignment in how data is defined, structured, governed, and moved across the program.

In this role you will,

- Define and maintain the Program's data architecture standards — including data modelling, data classification, data lineage, and data standards to support integration — ensuring all product and platform streams build to consistent, coherent data architecture practice and that emerging patterns & standards, or deviations, are surfaced to the Technical Design Authority for resolution or adoption.
- Represent data architecture interests within the Technical Design Authority, providing authoritative guidance on data-related architecture decisions and ensuring that cross-stream design choices do not create data coherence, quality, or security risks that compound over the life of the Program.
- Establish and maintain a program-wide canonical data model — including entity definitions, data dictionaries, and a business glossary — that reflects the operational reality of child protection, family violence, youth justice, and other program areas, and that all delivery teams are required to observe. Handover / work with BAU Information Management and Data Architect to ensure an ongoing capability to maintain the semantic definitions of the business data on an ongoing basis.
- Ensure the Enterprise Data Platform is designed for BAU transition from inception — defining the technical conditions for handover to ITS, the capability requirements the receiving organisation will need to operate and extend the platform, and the data governance structures that will govern the platform after the Program concludes.
- Provide leadership, oversight, and support to the Data Migration Lead regarding the architecture and design of all data migration from legacy systems into target platforms, establishing migration patterns,



data quality and validation standards, transformation logic governance framework, and the technical assurance framework within which migration delivery teams operate.

What you need to succeed

Technical expertise

- Data architecture leadership in large-scale digital transformation. Demonstrated experience as the data architecture authority in a large-scale, multi-team digital transformation program — defining data models, data standards, and data governance frameworks across parallel delivery streams, and ensuring that data design decisions made under delivery pressure do not create coherence, quality, or operability risks that accumulate over time.
- Experience working within an enterprise architecture governance framework — operating with delegated data architecture authority rather than as the sole technical decision-maker — and the professional maturity to exercise that authority without overreaching program boundaries.
- Enterprise data platform design and implementation. Deep technical expertise in the design and implementation of enterprise data platforms — including up-to-date data lakehouse and cloud-native data warehouse architectures, data ingestion and transformation pipelines, data cataloguing, lineage tracking, and analytics and reporting layer design.
- Demonstrated ability to make sound technology stack decisions for large-scale, long-lived government systems, including assessment of the operational sustainability and BAU maintainability of platform choices.
- Familiarity with the Microsoft Azure data platform ecosystem (including Azure Data Factory, Azure Synapse Analytics, Azure Databricks,



and associated services) is highly regarded.
- Data migration architecture and delivery in complex legacy environments. Demonstrated experience designing and governing the migration of data from complex legacy case management or enterprise systems — including defining migration architecture, transformation logic governance, data quality assurance frameworks, and validation standards.
- Data governance, data modelling, and canonical data design. Demonstrated ability to develop and maintain authoritative canonical data models and business glossaries for complex operational domains — including defining entity relationships, data classification hierarchies, and data lineage in environments where data is shared across multiple systems and organisational boundaries.
- Experience establishing data governance structures that survive program completion and operate effectively in a BAU environment, including stewardship models, data quality monitoring, and change management for data standards.
- Security, privacy, and compliance in government data environments. Demonstrated understanding of the data security and privacy obligations applicable to Victorian Government technology programs — including the Victorian Protective Data Security Standards (VPDSS), Health Records Act, and Privacy and Data Protection Act — and the ability to design data architectures that meet those obligations as structural requirements, not bolt-on controls.
- Experience designing data platforms and migration pipelines that handle sensitive personal and client data, including data relating to child protection, family violence, and youth justice clients, is essential.
- Stakeholder engagement and data architecture communication. Demonstrated ability to communicate complex data architecture decisions to non-technical stakeholders — including business owners, program leadership, and government governance bodies — in terms that enable informed decision-making.

📌 Lead Data Architect (Melbourne)
🏢 Hays
📍 Melbourne