Data Governance Analyst

As a Data Governance Analyst at GA Tech, your main responsibilities revolve around the operationalization of the enterprise data governance program. You will evaluate, update, and create enterprise data governance and management policies, guiding principles, standards, procedures, and processes. Collaborating with different teams to ensure effective documentation and presentation skills will also be a crucial part of your role.

To qualify for the Data Governance Analyst position at GA Tech, candidates should have at least three years of related experience, particularly in creating enterprise data governance policies and standards. A strong understanding of data governance frameworks, excellent attention to detail, and the ability to solve problems independently are essential attributes for this role.

Success in the role of a Data Governance Analyst at GA Tech requires a mix of technical and soft skills. Essential skills include the creation and management of data governance policies, strong problem-solving abilities, excellent attention to detail, and the capacity to adapt communication style to various audiences. Experience in the higher education sector would also be preferred.

At GA Tech, a Data Governance Analyst operates in a collaborative and dynamic environment. Expect to partner with multiple departments, tackle challenges that arise, and be flexible to change as the landscape of data governance evolves. The role demands adaptability and a comfort level with ambiguity in data management.

GA Tech's Data Governance Analyst is directly involved in integrating privacy and cybersecurity considerations into data governance policies. By focusing on the intersection of these areas, you’ll help ensure that the data governance framework not only meets institutional requirements but also aligns with best practices in privacy protection and cybersecurity.

A data governance framework is a structured approach that outlines how an organization manages and utilizes its data assets. It includes policies, standards, and procedures that ensure data is accurate, available, and secure. To effectively answer this during your interview, highlight your understanding of the components of a framework and how they interconnect.

In discussing your experience with enterprise data governance policies, provide specific examples of policies you've created or contributed to in previous roles. Emphasize the steps you took, the stakeholders involved, and the outcomes or impacts of these policies on the organization.

To ensure compliance, it’s critical to implement a regular review process, conduct training sessions, and maintain open communication with all stakeholders. During the interview, illustrate your methods for verifying adherence to standards and how you've addressed non-compliance issues in the past.

When asked about challenges, narrate a specific situation where you faced a data governance issue, explaining your role and the resolution process. Focus on your analytical approach, teamwork, and the lessons learned from the experience.

Familiarity with data governance tools is essential. In your response, mention specific tools you've used, such as data cataloging software or governance frameworks. Discuss how you utilized these tools to enhance data quality or compliance within your previous organizations.

Effectiveness can be measured through key performance indicators (KPIs) such as data quality, compliance rates, and user adoption of governance policies. Share examples of how you've tracked these metrics and any improvements observed as a result of your initiatives.

Staying updated on data governance practices is vital. Discuss your methods for continuous learning, whether through professional development courses, webinars, or industry publications. This shows your commitment to staying informed and applying best practices.

Communication is paramount in data governance to ensure that policies are understood and implemented effectively. Use your response to highlight examples where you've successfully communicated initiatives to diverse audiences and fostered collaboration among teams.

Effective prioritization is key in managing diverse projects. Discuss your approach to assessing project importance and deadlines, as well as any tools or frameworks you use to manage your workload efficiently.

When discussing the future of data governance, share insights on trends such as data privacy regulations and emerging technologies. Provide your perspective on how these developments will shape data governance practices and underscore your adaptability to future changes.