Assistant Director, Data Governance

[What the role is]
The National Library Board (NLB) nurtures Readers for Life, Learning Communities and a Knowledgeable Nation by promoting reading, learning and history through our network of 28 libraries across Singapore, the National Library and the National Archives of Singapore.

At NLB, you can look forward to a flexible, hybrid work environment with rewarding, impactful deliverables that improve the lives of the community. With caring colleagues, you will be in an ideal environment for professional development, innovation and impact.
We can offer you:
• A chance to Impact the Community, bridge gaps and empower everyone with the opportunity for learning and discovery.
• An opportunity to Innovate and Push Boundaries. We value ideas, curiosity and a passion for innovation to transform our libraries and archives.
• An organisation that Cares for your Growth and Wellbeing through investment in staff development and wellbeing in a supportive and collaborative environment.

The Data Governance AD is responsible for overseeing and implementing NLB’s data governance strategy, to ensure that NLB’s data capture, fusion and usage are reliable, secure, and of high quality, and to chart, document and iterate NLB’s overall data model.
Beyond the Data Office, you will work closely with the Technology Services Group (TSG) to develop the tools needed to effectively monitor the reliability and accuracy of our data.
The role also involves working with all NLB departments to establish and maintain data governance policies, procedures, and standards. You will be involved in upstream procurement, assessing the data capabilities of prospective vendors to evaluate their ability to provide NLB with data necessary for operations, reporting, and and analytics. You will also work closely with the eventual appointed vendors and TSG to ensure the accurate and timely transfer of data to the organization's data warehouse.

[What you will be working on]

1. Data Security and Privacy Policy:

• Develop and implement data security and privacy policies and procedures to protect sensitive information.
• Ensure compliance with relevant data protection regulations, such as IM8, or industry-specific standards.
• Conduct regular data risk assessments and audits to identify and mitigate potential data security vulnerabilities and potential data privacy risks.
• Collaborate with the IT department to implement and maintain appropriate data access controls and data encryption measures
• Train employees on data security/privacy best practices and raise awareness about the importance of data protection.

2. Data Quality and Vendor Management:

• Work closely with colleagues across various departments to understand their data requirements and ensure the capture of high-quality data. Ensuring the capture of high quality data includes upstream involvement in gathering and translating data requirements into procurement-related requirements and specifications.
• Develop and implement data quality standards, metrics and tools to measure and monitor the accuracy, completeness, and consistency of data.
• Work closely with vendors to establish data transfer processes and agreements that meet the organization’s data quality, analytics and security needs.
• Monitor and audit data transfers from vendors to ensure the timely and accurate integration of data into the organization’s data warehouse.
• Provide guidance and support to colleagues in their interactions with vendors to resolve data quality issues and improve data capture processes.

3. Data Governance Framework:

• Develop and maintain a comprehensive data governance framework that defines roles, responsibilities, policies, and procedures for managing data across the organization.
• Establish data governance committees and working groups to foster collaboration and decision-making on data-related issues.
• Define and implement data lifecycle management processes, including data creation, storage, sharing, archiving, and disposal.

4. Data Architecture and Integrated Data Model:

• Collaborate with IT and data architecture teams to ensure the development of a robust and scalable data architecture that supports enterprise-wide data integration and analysis.
• Oversee the development and maintenance of an enterprise-wide data model, comprising data dictionaries, metadata repositories, and other documentation (each maintained by respective responsible parties) to ensure a clear understanding of data definitions, lineage, and relationships.
• Work with data leads and subject matter experts to ensure the consistent application of data governance policies and standards across systems and processes.

5. Continuous Improvement:

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