Lead Data Manager – Metadata Governance | Baseline | Multiple Locations

Pinaka Technology Solutions; Canberra; Hybrid; AUD 150,000 - 210,000; Full time

Job summary

Services Australia is seeking a Lead Data Manager to drive end-to-end uplift of business metadata for priority data assets. You will oversee governance, registrars and developers, ensuring alignment with AI readiness and enterprise standards.

The role requires leadership of multi-disciplinary teams, strong data governance expertise and capability to manage complex data initiatives across the organisation.

Qualifications

• Demonstrated expertise implementing metadata registries (ISO/IEC 11179).
• Knowledge of metadata standards (ONDC, DCAT, National Archives requirements).
• Experience leading complex data, metadata or governance projects with multi-disciplinary teams.

Responsibilities

• Develop and maintain project scope, governance, success measures and delivery cadence.
• Prioritise high-value data assets across AI projects and programs.
• Set priorities, allocate resources and track delivery milestones and outcomes.
• Monitor progress with dashboards and capture risks, blockers, and registration status.
• Ensure alignment with agency objectives and AI readiness outcomes.
• Lead metadata landscape analysis, data dictionaries, lineage andDocumentation.
• Oversee metadata quality, consistency and registration readiness.
• Engage SMEs, data engineers and analysts; manage team performance.
• Provide training in ISO/IEC 11179 and metadata standards.
• Transition records to sustainable stewardship and maintenance.

Skills

ISO/IEC 11179 implementation

Metadata standards knowledge

Leadership of complex projects

Data governance expertise

Analytical capability

Stakeholder management

Excel & project tracking

Learning agility

Analytics/AI data initiatives

Job description

Lead Data Manager

Australian citizenship required. Must be able to obtain Baseline security clearance.

Location: Brisbane/Canberra/Melbourne/Adelaide/Hobart/Cairns/Robina (Hybrid).

RFQ Details

• RFQ ID: LH-08365
• Agency: Services Australia
• Closing Date: Tuesday, 10 November 2026 – 11:59pm (Canberra time)
• Estimated Start Date: Tuesday, 01 December 2026
• Initial Contract Duration: Up to 12 months
• Extension Term: Other
• Experience Level: Lead – EL1 equivalent
• Security Clearance: Must be able to obtain Baseline security clearance
• Location of Work: QLD, ACT, VIC, SA, TAS
• Working Arrangements: Hybrid. The Labour Hire Worker is expected to work onsite for the first 6 weeks before a hybrid flexible working arrangement can be considered, unless otherwise negotiated. A hybrid flexible working arrangement may then be considered, ensuring the Labour Hire Worker's residing address is within reasonable travel time and distance of the RFQ location to present onsite in cases of emergency or to meet business requirements. The location is the capital city of selected state/s plus Cairns and Robina.
• Maximum Hours: 50 hours per week

Job Details

Metadata Project Lead

Data Managers support organisations with the sourcing, acquisition, management, integration and sharing of data to provide business insights and drive data-based decision making.

As the Data Manager you will be accountable for the end-to-end uplift of business metadata for priority high-value data assets. The role plans and governs the body of work, sets priorities, leads metadata registrars and developers, and ensures delivery is aligned with strategic objectives, AI readiness outcomes and applicable metadata standards.

Primary Focus: Project leadership, governance, delivery assurance, team leadership, strategic stakeholder engagement and quality oversight.

Key Duties and Responsibilities

Project Governance and Delivery Leadership

• Develop and maintain the project scope, governance arrangements, success measures, delivery cadence and reporting requirements.
• Confirm and prioritise high-value data assets across approved AI projects and relevant program areas.
• Set work priorities, allocate resources and maintain accountability for delivery milestones and outcomes.
• Track progress, quality, blockers, risks, coverage and registration status through fit-for-purpose project trackers or dashboards.
• Ensure delivery remains aligned with agency strategic objectives and AI readiness outcomes.

Metadata Leadership and Quality Assurance

• Lead analysis and curation of the current metadata landscape, including existing metadata records, Enterprise Data Warehouse artefacts, data dictionaries, lineage information, source-system documentation and project materials.
• Oversee assessment of metadata coverage, gaps, duplication, quality issues and terminology inconsistencies across related data assets.
• Direct harmonisation of definitions, naming, business context and governance attributes where appropriate.
• Ensure new metadata uses clear, consistent, plain-English definitions and descriptions suitable for business and technical audiences.
• Review and assure the consistency, completeness and quality of metadata before or during registration.

Stakeholder and Team Leadership

• Identify and engage key subject matter experts, data stewards, data engineers and analysts, and AI project contacts.
• Lead and manage metadata registrars and metadata developers, including performance, attendance, workload, health and wellbeing.
• Deliver training and capability uplift in ISO/IEC 11179 and agency metadata standards.
• Oversee stakeholder validation, metadata registration feedback and resolution through to agreed status.
• Transition registered records to sustainable stewardship and maintenance arrangements.
• Lead and support operations of the team including monitoring business performance, setting priorities, and managing resources and workflow.
• Develop staff capability through coaching, mentoring and succession planning to increase performance, engagement and retention.
• Undertake and assist with business management and workforce planning.
• Prepare and review a range of written material including technical and corporate documentation.
• Report on the achievement of business outcomes, key performance indicators and quality assurance to manage overall performance.
• Assist with the development of strategies, operational policy and procedures and change initiatives.
• Act with integrity by promoting workplace practices aligned with the APS Values and the APS Code of Conduct.
• Exercise delegation in accordance with legislation and guidelines.

Technical Skills

• Demonstrated expertise implementing the ISO/IEC 11179 standard for metadata registries.
• Knowledge of relevant metadata and information management standards, including ONDC metadata attributes, National Archives of Australia requirements and Data Catalogue Vocabulary (DCAT).
• Demonstrated experience leading complex data, metadata or governance projects and multidisciplinary teams.
• Data governance and data management expertise.
• Strong research, synthesis and analytical capability.
• High-level written and verbal communication and stakeholder-management skills.
• Advanced Microsoft Excel and project tracking skills.
• Ability to quickly acquire knowledge of agency programs and the agency data landscape.
• Experience supporting analytics, automation or AI-related data initiatives.

About the Organisation

Services Australia is at the frontline of government service delivery, supporting millions of Australians, and is front and centre of a vision to be a world leader in government service delivery. It's using cutting-edge technology to build world class platforms and capabilities to help Australians get on with their lives.

Selection Criteria

The buyer has specified that each candidate must provide a one page pitch to address all criteria specified. This is equal to 5000 characters.

Essential Criteria

1. Data access: Level 3 (DCF)

Can mitigate issues arising from different access approaches Can make and justify recommendations for data access Can provide actionable strategic advice on data access

2. Data and information management: Level 3 (DCF)

Is an expert resource for implementing and shaping the organisation's strategic use of data and information management good practice, and can advise others. This includes requirements relating to data access, data security, privacy and ethics Represents a point of contact for data and information management leads in other organisations

3. Data classification: Level 3 (DCF)

Is an expert resource on data classifications and coding protocols and advises others Can employ conceptual frameworks in support of data classification and coding

4. Data collection: Level 3 (DCF)

Is an expert resource in all aspects of data collection, including why data is collected and the roles associated with collection Can make justifiable decisions about how data is collected Can write custom scripts and code (programming language) to collect data

5. Data collection methodology: Level 3 (DCF)

Is an expert resource on data collection methodology Can make justifiable recommendations to address data collection issues Maintains understanding of new trends and innovations relating to data collection methodology (including Artificial Intelligence-based technologies) and develops own capabilities in these where relevant

6. Data editing: Level 3 (DCF)

Is an expert resource on different methods of data editing and advises others Can assess current editing methods critically Can build capability of others in data editing concepts and methods

7. Data governance: Level 3 (DCF)

Is an expert resource in data governance and can formulate and advise on data governance policies and contribute to the structure of organisational data governance frameworks (includes data access, data security, privacy and ethics) Representatives a point of contact for data governance leads in other organisations Maintains awareness of new legislative requirements and trends that impact good data governance and ensures organisational compliance with these (includes data access, data security, privacy and ethics) Can provide data governance thought leadership across broader data use contexts

8. Data integrity and quality assurance: Level 3 (DCF)

Is an expert resource in the use of measures for data quality assurance, the interaction of those measures, and their application in conjunction with one another Can advise others on the use of data quality measures to make accurate assessments of data fitness-for purpose (including trustworthiness and accuracy) Is an expert resource on ensuring data integrity across its lifecycle, and advises others

9. Data outputs, products or services: Level 3 (DCF)

Has expert knowledge about the production of a data output, product or service Provides expertise in developing new products or data services to meet evolving requirements, needs and opportunities. Can build the capability of others in the delivery of data outputs, products or services

10. Data use and re-use: Level 2 (DCF)

Understands and can articulate the value of data in terms of use and re-use Implements a variety of techniques to ensure data is open and can be used beyond the specific purpose for which it was collected, in accordance with legislative requirements and organisational guidelines (includes data sharing legislation)

11. Identify research questions: Level 2 (DCF)

Can identify and structure relevant research questions for specific needs, and develop the approach and specific measures to resolve those questions

12. Integrate data: Level 3 (DCF)

Can perform and provide expert advice on data integration Can build capability of others in understanding and applying good data integration practice and principles Can write custom scripts and code (programming language) to integrate data Maintains understanding of new trends and innovations relating to integrating data (including Artificial Intelligence-based technologies) and develops skills in these where relevant

13. Metadata - Describe and summarise data : Level 2 (DCF)

Can use various summary options to effectively describe data, and explain and justify those choices Follows organisational standards and procedures relating to metadata creation, storage and use. Can access metadata and use the descriptors to better understand existing data and effectively use it.

14. Sourcing and use of administrative data: Level 3 (DCF)

Is knowledgeable about multiple sources of administrative data Can advise on how the data has been used to produce new insights Provides expertise to identify new sources of administrative data as well as uses for that data Can write custom scripts and code (programming language) to source and combine administrative data Maintains understanding of new trends and innovations relating to sourcing of administrative data(including Artificial Intelligence-based technologies) and develops capabilities in these where relevant

15. Value organisational data as assets: Level 2 (DCF)

Has extensive knowledge of the organisation's data assets, including a comprehensive understanding of how their fitness for purpose translates to value for the organisation Promotes opportunities for using data to support decision making, advice and research Considers the broader environment and context when drawing or interpreting insights from data. Uses these insights to make informed, evidence-based decisions and recommendations, and act accordingly