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, 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.

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📌 Data EngineerFusion (Canberra)
🏢 Indigitise
📍 Canberra