Lead Data Manager

Data Management / Data Assurance 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 a data assurance lead in the Data Assurance section, you will be a data management and data ethics champion, working under limited direction of the Director and senior leaders. You will apply your knowledge and understanding of data management and data ethics to assess the requirements of data through AI and other complex data initiatives to ensure data is appropriately managed throughout its lifecycle and used ethically. You will support the delivery of trusted, explainable and accountable data that benefits our customers. You will do this via the application of our data trust and ethics and data management processes and tools, aligned to our overarching Frameworks. You will enable and empower business teams to implement data management and data ethics by design to build community trust and confidence in our services. In collaboration you will support the consideration in the enhancement of our tools to more advanced technology and you will use your data assurance expertise to advise on potential enhancements to processes to support emerging AI. You will use your knowledge and expertise to coach, develop and inspire team members within the Section and beyond in data assurance with a customer centric focus. You will be responsible for conducting reviews and providing recommendations and briefs for senior leaders and committees. Extensive knowledge of: • Data management fundamentals and how they apply across a broad range of disciplines (expert understanding) • Relevant data management approaches and frameworks Knowledge / Qualifications Ability to quickly acquire knowledge of the following: • Legislation, policies, procedures and information management relevant to the work area • The agency’s strategic direction, priorities and functions • 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. Key duties and responsibilities Duties may include some or all of the following: Data Ethics and Data Management • Apply experience in risk-based governance frameworks and data ethics to support assurance activities across data and AI-enabled initiatives • Develop data assurance and AI processes and practices. • Assess data initiatives to identify data management, trust and ethics risks, and provide clear, impartial recommendations to resolve issues in line with the agency’s Data Governance Framework and data trust and ethics principles. • Provide user-centred advice on the ethical, trust and data management implications of new technologies, emerging AI use cases and changing work practices • In collaboration, support improvement of data assurance processes and practices, including modernising tools to support transparent, accountable and explainable AI • Develop, implement and maintain data management documentation and embed best practice processes and procedures Communication and Stakeholder Engagement • Prepare high-quality briefs, recommendations, formal communications and presentation materials for senior leaders, committees and stakeholders, often within short timeframes • Communicate complex data governance, data ethics and assurance concepts clearly through conversations, documentation and presentations • Communicate effectively and foster partnerships with internal and external stakeholders to impart expertise and inspire others Planning; judgement etc • Demonstrate initiative, professional judgement and sound problem-solving skills, including the ability to • Research projects and initiatives, assess risks and recommend practical action • Plan and manage work priorities for yourself and the team, including developing clear work plans, timeframes and supporting documentation • Develop staff capability through coaching, mentoring and succession planning to increase performance, engagement and retention • 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. • Champion data management and drive a culture of valuing data as an asset • Translate complex data management concepts to stakeholders • Work with data and data analytics tools with an expert level of proficiency • Apply expert skills in data quality, data cleansing and data validation • Develop long term plans for the team and manage work in the context of business priorities • Manage, coach and guide team learning and development • Make decisions based on professional judgement and risk evaluation, and in the context of the situation and environment • Embrace an agile mindset, working within, or with multi-disciplinary teams. 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 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) Represents 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 7. 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 8. 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 9. 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) 10. 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. 11. 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 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 06 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