Application closing date: Tuesday, 15 July 2025 • 11:59pm, Canberra time
Estimated start date: Tuesday, 12 August 2025
Location of work: ACT
Working arrangements: Hybrid working arrangements (i.e. a combination of onsite attendance at an AEC office and remote working) will be considered at the discretion of the Hiring Manager with a typical 3 days in the office and 2 days working from home.
Length of contract: Until 30 June 2026
Contract extensions: 1x 12 months
Security clearance: Must have a Baseline clearance
Rates: $110 - $130 per hour (inc. super)
Enterprise Strategy and Transformation Division (ESTD) The ESTD is one of two divisions within the Australian Electoral Commission’s (AEC) Enterprise Transformation Group (ETG) established to drive the AEC’s transformation agenda, and to deliver the Election Systems Modernisation Program (Indigo Program) on behalf of the agency.
Indigo Program (Tranche 2) The Indigo Program is a large-scale transformation program to modernise business capabilities and replace core election ICT systems with a citizen-centric, agile technology platform. The Program will transform the AEC’s delivery of electoral services and ensure ongoing integrity of the electoral system. Tranche 2 comprises a variety of work packages with a focus on business process re-engineering, data management, legislative compliance and replacing aging systems.
The AEC is seeking a Lead Data Modeller who are computer systems engineers who will design and implement data modelling solutions using relational, dimensional, and NoSQL databases. To ensure success as the lead data modeller, the position holder should have in-depth knowledge of data warehousing, modelling techniques covering conceptual, logical and physical representations of transactional, analytical and big-data processing systems. as well as expert communication skills. Ultimately, the lead data modeller should be able to design models that reduce data redundancy, streamline data movements, and improve enterprise information management

Key duties may include, but are not limited to:

• Undertaking work that is moderately complex to complex and/or sensitive in nature, under limited direction, utilising expertise and knowledge within the area of data modelling
• Analysing and translating business needs into long-term solution data models.
• Evaluating existing data systems.
• Working with the development or Agile Delivery team to create conceptual data models and data flows.
• Developing best practices for data coding to ensure consistency within the system.
• Employing data modelling techniques to develop analytical solutions and make recommendations to business stakeholders.
• Establishing sustainable automatic analytical processes.
• Collaborate with stakeholders and data professionals to identify and support process improvement opportunities within data governance and quality frameworks.
• Reviewing modifications of existing systems for cross-compatibility.
• Implementing data strategies and developing physical, conceptual and logical data models.
• Updating and optimizing local and metadata models.
• Evaluating implemented data systems for variances, discrepancies, and efficiency.
• Troubleshooting and optimising data systems.

HOW TO APPLY

Please provide an updated CV (a maximum of 3 pages) to reflect your suitability to the role based on the job description. You will also need to complete a response to the Essential and Desirable criteria above in a summary no more than 5000 characters in total

• Undertaking work that is moderately complex to complex and/or sensitive in nature, under limited direction, utilising expertise and knowledge within the area of data modelling
• Analysing and translating business needs into long-term solution data models.
• Evaluating existing data systems.
• Working with the development or Agile Delivery team to create conceptual data models and data flows.
• Developing best practices for data coding to ensure consistency within the system.
• Employing data modelling techniques to develop analytical solutions and make recommendations to business stakeholders.
• Establishing sustainable automatic analytical processes.
• Collaborate with stakeholders and data professionals to identify and support process improvement opportunities within data governance and quality frameworks.
• Reviewing modifications of existing systems for cross-compatibility.
• Implementing data strategies and developing physical, conceptual and logical data models.
• Updating and optimizing local and metadata models.
• Evaluating implemented data systems for variances, discrepancies, and efficiency.
• Troubleshooting and optimising data systems