Job no: 533474
Work type: Full Time
Location: Sydney, NSW

Categories: Library

• Employment Type: Full-Time (35-hour week)
• Duration: Continuing Role
• Remuneration: $127,351+ 17% superannuation and leave loading (Level 8)
• Location: Kensington NSW (hybrid)

WHY YOUR ROLE MATTERS

The Manager, Electronic Resources & Data Quality plays a critical leadership role in ensuring the accuracy, completeness, consistency, and discoverability of the Library’s collection data. This includes, but is not limited to, bibliographic records, digital collection metadata and Indigenous cultural and intellectual property (ICIP) elements.
The Manager leads the development, implementation, and oversite of data quality standards, guidelines, and workflows, leveraging their expertise in library science principles, metadata best practices, and data management technologies. This position leads initiatives to enhance data integrity and interoperability, support data-driven decision-making, and foster a culture of data excellence across the Library with a forward-looking perspective on how Artificial Intelligence (AI) can both impact and enhance data quality standards.
The role of Manager, Electronic Resources & Data Quality reports to the Associate Director, Electronic Resources and has five direct reports. This a replacement role – full time ongoing.

WHAT YOU WILL DO

• Manage and lead a team of professional staff to build a positive and forward-thinking approach to the delivery of excellence in data quality and electronic resource access
• Develop, implement, and maintain a comprehensive data quality strategy for the library, aligned with institutional goals and industry best practices
• Lead initiatives to update and enhance metadata for Indigenous materials using culturally appropriate terms
• Establish and document data quality standards, policies, and procedures for various data types and systems within the Library environment
• Lead the design and continuous improvement of efficient acquisition workflows
• Oversee and actively participate in data enrichment, and remediation activities to resolve identified data quality issues
• Maintain a high level of knowledge around emerging trends and best practices in data quality management, library metadata standards, cataloguing principles, and relevant technologies.
• Leverage library systems, data analysis tools, and scripting languages to monitor data quality, automate checks, and facilitate data remediation
• Explore, evaluate, and recommend AI/Machine Learning tools and techniques to enhance data quality processes
• Contribute expertise and knowledge and team input to the Library’s strategic planning processes and convene cross-library working groups as required