Data Engineer - G0 Fusion

Indigitise; Canberra; On-site; AUD 120,000 - 180,000; Full time

Job summary

Indigitise in Canberra is seeking a seasoned Data Engineer to design and implement data integration pipelines sourcing logistics data from legacy systems.

You will collaborate with Business Analysts, Data Architects and developers to map data structures across logistics, inventory and asset management, and devise data object designs for relational and data mesh environments, supporting Army analytical products.

Qualifications

• Minimum 5 years dedicated data engineering experience across: SQL development including 3NF and STAR schema design.
• Experience migrating legacy data warehouse environments to analytical platforms.
• Datamart design, build and testing.
• SQL code optimisation and refactoring.
• Python scripting and data transformation.
• Experience with Data Vault 2.0 patterns and data mesh structures.
• Experience with logistics systems and SAP context.
• Experience with Defence or related industries such as capability development and delivery.
• Experience with sensitive datasets (PII/PII) and security requirements.
• Experience with large teams on complex analytics projects.
• Familiarity with Cloudera data analytics suite and Databricks.

Responsibilities

• Design and implement data integration pipelines sourcing logistics and sustainment data from legacy applications.
• Collaborate with stakeholders to analyse data structures and develop mappings across logistics, maintenance, inventory, supply chain and asset management.
• Develop data object designs for relational and data mesh environments within the data generation lifecycle for Army analytics.
• Support legacy data warehouse migration to Defence enterprise data mesh architecture.
• Design and develop domain-aligned data products supporting self-service analytics, reporting and decision support.
• Transform landed data into centrally managed warehouse STAR schema and governed data products.
• Support federated governance, data discovery and enterprise-wide data sharing capabilities.
• Apply DevSecOps, CI/CD and pipeline execution; ensure governance, security and information management compliance.

Skills

SQL development

3NF design

STAR schema

Data mesh concepts

Python scripting

Data Vault 2.0

Databricks

Hive/Impala

Data migration

Tools

Cloudera CDV

Hive

Impala

Ozone

Iceberg

Spark

Databricks

Job description

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.