Senior Data Manager

Senior Data Analyst Data Managers support organisations with the sourcing, acquisition, management, integration and sharing of data to provide business insights and drive data-based decision making. Data Foundations for AI (D4AI) Data Managers analyse datasets with a variety of tools to research and solve organisational issues and identify trends and insights to support organisational outcomes. Data Managers understand customer data requirements and can analyse matching scenarios within the data management tools. The role assists with the management of the organisation’s data assets in order to improve and maintain data quality. Data Managers work under the limited direction of senior staff. They exercise both initiative and judgement in the interpretation of policy and in the application of practices and procedures. Decision making is dependent on judgement, skills and knowledge. Senior Data Analysts manage and organise their own work in the context of competing priorities, including contributing to business planning, changes in workplace practices and business improvement strategies. The Data Managers will contribute to the delivery of the Data Foundations for AI (D4AI) project by leading data and project activities that support the improved governance, management and visibility of data in Services Australia. The project will improve the agency’s ability to understand the quality of data holdings to reduce the risk of inappropriate or biased use of high-value data for analytics, automation and AI-enabled decision-making. As a Data Manager you will contribute to planning, implementing and reporting on the body of work to ensure alignment to strategic objectives and AI readiness outcomes. Working with a diverse range of stakeholders, you will analyse data assets and gather business requirements to create, implement and socialise data quality rules. You may also lead a team of staff. Working with a diverse range of stakeholders, the Data Managers will analyse data assets within the agency, identify data governance and management opportunities, manage requirements, support the execution of project activities, and develop recommendations that support informed decisionmaking and successful project delivery. The Data Managers will have the opportunity to influence and actively contribute to the rollout of core platform capabilities such as data lineage, data quality and metadata management. The rollout and expansion of these capabilities will be a critical enabler to support enterprise-wide data governance and future AI initiatives in the agency. The role provides an opportunity to influence strategic outcomes, drive continuous improvement, and help shape the agency’s approach to data governance and management via D4AI in a complex and evolving data and AI environment. • Experience with data governance tools or platforms, such as Collibra, Informatica, IBM Knowledge Catalogue or similar. • Ability to use data querying such as SQL, Python or similar to query and analyse data stored across agency data platforms. Required skills and knowledge include: • Demonstrated understanding of data governance and data management concepts, including metadata management, data quality, data lineage and data stewardship. • Understanding of enterprise data management platforms and their role in supporting data discovery, governance and reuse. • Experience analysing business needs, gathering requirements and translating them into practical data governance or platform requirements. • Ability to assess data assets, business processes and operational systems to identify governance, quality or metadata improvement opportunities. • Strong research, analysis and problem-solving skills, including the ability to develop evidence-based recommendations. • Experience supporting project delivery activities, including planning, documentation, testing, implementation and continuous improvement. • Strong stakeholder engagement skills, including the ability to work with business and technical teams to clarify needs, manage expectations and support adoption. • Strong written and verbal communication skills, including the ability to prepare clear reports, briefings and documentation for senior stakeholders. • Ability to manage competing priorities, work independently and contribute effectively in a complex project environment. • Proficiency in Microsoft Excel to support analysis, reporting, tracking and documentation. Ability to: • Understanding of data governance platforms, data management, metadata standards, data quality and/or data lineage • Think strategically and consider the issues and impacts on work and work area • Supervise, guide and develop staff capability • Develop and maintain stakeholder relationships • Identify risks and steps required to mitigate them • Manage conflict using appropriate strategies and determine issues for escalation • Prioritise competing tasks and work collaboratively to deliver quality projects outcomes • Communicate effectively and adapt communication style appropriate to the audience • Establish clear work plans and time frames for self and others • Undertake objective, systematic analysis and draw accurate conclusions based on evidence • Research and make decisions based on good judgement, expertise and knowledge • Work independently under limited direction and act collaboratively • Work as an effective team leader and support staff to achieve quality outcomes • Adapt to change and uncertainty, and support staff through the process • Identify and consider expectations and concerns.  Ability to quickly acquire knowledge of: • Frameworks, legislation, policies, procedures and information management requirements relevant to the work area • The agency’s privacy, ethics, workplace health and safety and security protocols • Relevant business systems and tools. Desired skills and knowledge include: • Knowledge of data governance frameworks, data operating models, metadata standards or relevant legislation and policy settings. • Understanding of data quality dimensions, data lifecycle management and information management principles. • Experience supporting change management, user guidance, training or adoption activities for new data or digital capabilities. Key duties and responsibilities Duties may include some or all of the following: • Lead data analysis activities to support the delivery of the D4AI project. • Work with stakeholders to understand business needs, gather requirements, and develop practical data governance solutions. • Ensure the alignment of business data requirements with the enterprise application. • Establish and maintain data business rules and security specifications within the platform. • Develop a strong understanding of the platform capabilities and assess opportunities and limitations to support enhanced data governance and management practices via the platform. • Contribute to the development and implementation of improvements and best practice in processes and procedures. • Assess how the platform rollout and usage aligns with policies, frameworks and the data operating model. • Evaluate, define, integrate and organise data coming from multiple operational systems. • Support the development and maintenance of project documentation, requirements and analysis artefacts. • Support project planning, testing, implementation and continuous improvement activities. • Build strong stakeholder relationships and manage competing priorities to achieve project outcomes. • Support the rollout and ongoing maintenance of core platform capabilities related to metadata management, workflow management, data lineage and data quality, which may include providing training to agency users. • Prepare correspondence such as reports, requirements artefacts and business process documentation for review by executive level staff. • 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. 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 2 (DCF) Has a comprehensive knowledge of protocols associated with data access. 2. Data and information management: Level 2 (DCF) Has a comprehensive knowledge of the organisation's data and information management principles and guidelines and can apply them to support good data practice. This includes requirements relating to data access, data security, privacy and ethics Can advise others on the proper application of data and information management concepts 3. Data classification: Level 2 (DCF) Has a comprehensive knowledge of data classifications and coding protocols Knows where to obtain expert advice about coding and classifications where needed 4. Data collection: Level 2 (DCF) Has a comprehensive knowledge of the full range of data collection options, including costs and benefits Knows how to mitigate issues arising from different collection modes Is able to understand and amend existing code (programming language) to collect data 5. Data collection methodology: Level 2 (DCF) Has a comprehensive knowledge of relevant data collection methodologies Can make and justify recommendations of various modes of collection 6. Data editing: Level 2 (DCF) Has a comprehensive knowledge of the different editing methods at their disposal Understands why different methods are used and can describe the limitations of each method Knows where to find expert advice about data editing as required 7. Data governance: Level 2 (DCF) Can contribute to the creation of internal policies in support of data governance in alignment with current legislative and organisational requirements (includes data access, data security, privacy and ethics) Can educate others in the importance of good governance practice 8. Data integrity and quality assurance: Level 2 (DCF) Can describe and produce data quality measures for the outputs they produce Has a comprehensive knowledge of relevant data quality measures and can use them to make accurate assessments of data fitness-for purpose (including trustworthiness and accuracy) Has a comprehensive understanding of relevant data integrity principles and practices, and uses them to maintain the integrity of organisational data 9. Data outputs, products or services: Level 2 (DCF) Is responsible for the production of a data output, product or service. Can create data outputs or products and deliver data services in accordance with established processes and systems, and can explain decisions made at all stages 10. Data use and re-use: Level 1 (DCF) Understands the data they work with can be used more widely and is aware of relevant data sharing legislation Is familiar with basic data sharing guidelines and organisational procedures to support the re-use of their data by others 11. Identify research questions: Level 1 (DCF) Can formulate research questions with guidance and consider the appropriate approaches and measures to resolve those questions 12. Integrate data: Level 2 (DCF) Can perform data integration using standard tools and can implement quality controls Knows where to obtain expert advice on data integration as needed Is able to understand and amend existing code (programming language) to integrate data Can assess datasets' suitability for linkage and extract appropriately prepared datasets 13. Metadata - Describe and summarise data : Level 1 (DCF) Understands there are different ways to summarise data and has a basic understanding of commonly used metadata options Understands the concept of metadata, including its purpose and benefits 14. Sourcing and use of administrative data: Level 2 (DCF) Is knowledgeable about various sources of administrative data and can explain their limitations Has a strong understanding of the advantages and disadvantages of using administrative data, including in relation to survey data Can assess the utility of different sources of administrative data for a particular purpose Understands and can amend existing code (programming language) to source and combine administrative data 15. Value organisational data as assets: Level 1 (DCF) Is familiar with organisational data assets relevant to their work Understands how those assets contribute value to the organisation Actively looks for opportunities to use data to support decision making, advice and research Uses insights from data to make informed, evidence-based decisions and recommendations, and act accordingly Opportunity summary Sellers can submit Up to 3 candidates Number of sellers invited Between 5 and 10 Number of candidates submitted Fewer than 10 RFQ closing time 02 Weeks 00 Days 12 Hours Send us feedback About Accessibility Privacy Terms of use Disclaimer and copyright An initiative of the Digital Transformation Agency The Australian Government acknowledges the Traditional Owners of Country throughout Australia and acknowledges their continuing connection to land, waters and community. We pay our respects to the people, the cultures and the Elders past and present. © Commonwealth of Australia