Under direction of the Commonwealth, undertake the following duties: Enterprise Data Migration • 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, STAR schema design and implementation, in a data warehouse context.
· Agile development, preferably Scrum.
· Experience migrating legacy data warehouse environments to preferably up-to-date analytical platforms or experience with large application data migration or refactoring.
· Python scripting, data engineering or data analysis · Data DevOps including ETL/ELT pipeline execution, data quality controls / verification · Datamart design, build and testing.
· SQL code optimisation and refactoring.
· Python scripting and data transformation.
Desirable · Experience with Data Vault 2.0 patterns, data mesh structures · Experience with the logistics systems and logistics business domain, especially in a SAP enterprise context.
· Experience with Defence or related industries such as capability development and delivery, sustainment or operational planning.
· Experience with data engineering of sensitive datasets at SECRET, protected identities (PI) and personality identifiable information (PII) · Working in a large team on a complex application 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 Databricks including data mesh concepts.

📌 Data EngineerFusion (Canberra)
🏢 Indigitise
📍 Canberra