Canberra, Australia | Posted on 10/11/2026
Under direction of the Commonwealth, undertake the following duties:
Design and implement data integration pipelines that source logistics and sustainment data from legacy applications
Collaborate with stakeholders including Business Analysts, Data Architects and developers, analyse logistics, maintenance, inventory, supply chain, procurement and asset management data structures and develop data mappings
Generate and revise suggested data object designs across relational and data mesh environments as part of the prescribed data generation life cycle for Army analytical products
Research and develop data migration strategies, cutover approaches and ongoing integration mechanisms between legacy data source and target data sources plus platform migration.
Support testing, verification and operational acceptance of migrated logistics datasets.
Legacy Data Warehouse to Enterprise Data Mesh Migration
Support the migration of analytical data assets, from Army legacy data warehouse into a Defence enterprise data mesh architecture.
Design and develop domain-aligned data products that support self-service analytics, reporting and decision support capabilities.
Transform landed data into centrally managed warehouse STAR schema plus governed, reusable data products aligned to Data Mesh principles.
Support implementation of federated governance, data discoverability and enterprise-wide data sharing capabilities.
Data Product and Data Mart Development
Design and develop business-ready data marts and analytical models supporting:
Organisational structure and hierarchy management
Logistics and inventory management
Maintenance and sustainment management
Equipment readiness and asset visibility
Workforce and establishment reporting
Operational planning and decision support




Develop conformed dimensions and shared business entities to ensure consistency across analytical domains.
Support data engineering for dimensional, data vault and hybrid modelling approaches as appropriate to support enterprise analytics requirements.
Analyse enterprise semantic-ready datasets suitability for Army use cases.
Data Engineering and Platform Development
Apply DevSecOps, CI/CD and pipeline execution where appropriate.
Ensure compliance with enterprise governance, security, privacy and information management policies.
Including standards for data quality, stewardship and lifecycle management, and master data management.
Requirements
Minimum 5 years dedicated data engineering experience across:
SQL development including 3NF design, STARschema design and implementation, in a data warehouse context.
Experience migrating legacy data warehouse environments to preferablymodern analytical platforms or experience with large application data migrationor refactoring.
Datamart design, build and testing.
SQL code optimisation and refactoring.
Python scripting and data transformation.
Experience with Data Vault 2.0 patterns, datamesh structures
Experience with the logistics systems andlogistics business domain, especially in a SAP enterprise context.
Experience with Defence or related industriessuch as capability development and delivery, sustainment or operationalplanning.
Experience with data engineering of sensitivedatasets at SECRET, protected identities (PI) and personality identifiableinformation (PII)
Working in a large team on a complexapplication in a decision support or data analytics context.
Cloudera data analytics suite (CDV, CML etc)including Hive, Impala, Ozone, Iceberg, Spark or contemporary suite eg Databricksincluding data mesh concepts.
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📌 Data EngineerFusion (Canberra)
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