
Data Modeller
4 weeks ago
Role title
Data Modeler
Contract type and termInitial 6-month contract with likely extensions. Very Likely
Work locationHybrid across Australia. Candidates may base themselves in ACT, NSW, QLD or VIC. Occasional on-site days in Melbourne or Canberra as required.
Security clearanceAustralian Citizenship is mandatory. Active Baseline or higher (NV1 or NV2) preferred. Client will sponsor upgrades where feasible.
About the roleThe Data Modeller designs, implements and documents enterprise-grade data architecture spanning relational, dimensional and NoSQL domains. You will enable information management, analytics, machine learning and digital service delivery for federal clients.
Key responsibilities- Translate business rules into conceptual, logical and physical data models for OLTP, OLAP, graph and NoSQL platforms.
- Deliver new data strategies, flows and models across cloud and on-prem domains.
- Define and enforce data modelling standards, tools and governance.
- Identify and design interfaces, automated data loads, security controls and visualisation pathways.
- Perform hands-on modelling, performance tuning, POCs and environment configuration.
- Work independently to reduce delivery risk and meet aggressive federal project timelines.
- 6-8+ years in data modelling, including Data Vault 2.0 and Star/Snowflake.
- 5+ years across major DBMS platforms (MySQL, SQL Server, Postgres, Oracle, Teradata, Snowflake, DB2, Netezza).
- 3+ years in cloud data warehouses / lakes, preferably AWS, plus Databricks exposure.
- Strong SQL, with Python or JavaScript scripting ability.
- Proven conversion of relational models to XML or JSON and vice versa.
- 5+ years with ERWin, ER Studio or PowerDesigner.
- Experience in Agile or Scrum delivery.
- Ability to communicate complex concepts to mixed technical audiences.
- Bachelor's degree in Computer Science, Information Systems or related field.
- Government / Fed Services or Health domain knowledge.
- Power BI visualisation expertise.
- Experience uplifting internal teams through knowledge transfer.
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