Data Governance Architect

As a Data Governance Architect at our company in Jamestown, NC, you will be responsible for developing and implementing organization-wide strategies for data storage, security, and management. This involves creating policies for data quality and integrity, classification, auditing, and more. You'll also have the opportunity to lead initiatives that enhance our data architecture and ensure compliance with industry standards.

To be a successful Data Governance Architect with us, you need at least a Bachelor's Degree along with 6 years of relevant experience. A strong foundation in data governance, data architecture, and project management is essential for this role. Familiarity with data security regulations and best practices will also be beneficial as you lead various projects.

In the role of Data Governance Architect, you will closely collaborate with data engineering and analytics teams. This partnership is critical during peak demand times when you will assist with ETL processes and platform architecture activities to ensure seamless operations. Your ability to coordinate and communicate effectively will drive the success of cross-functional initiatives.

A typical day for a Data Governance Architect involves reviewing data warehouses to ensure security, developing data management strategies, and optimizing information flow across the organization. You will spend time evaluating new data sources and developing policies to maintain high standards of data quality, and may also conduct audits to assess compliance with established guidelines.

As a Data Governance Architect, you'll have ample opportunities for career advancement within our tech company. You can progress into senior leadership roles within data governance or transition into broader data strategy positions. Continuous professional development and involvement in innovative projects will also enhance your resume and broaden your career prospects.

In answering this question, highlight specific frameworks you've worked with, such as DAMA-DMBOK or GDPR. Discuss how you implemented these frameworks in past roles to enhance data quality and compliance, illustrating your understanding of the importance of governance in data management.

Explain your methodology for conducting data quality audits, including specific metrics and tools you use to assess data integrity. Share examples of past audits and how your findings led to process improvements.

Discuss preferred tools like Collibra or Informatica and explain why these tools align with your data governance goals. Mention features that have helped enhance your past projects and how they ensure compliance and efficiency.

Talk about your strategies for ensuring data security, including access controls, encryption, and compliance with regulations. Provide examples of how you have identified and mitigated security risks in past roles.

Use the STAR method to outline a specific instance where you assessed a data management process, identified inefficiencies, and implemented changes that improved data flow or quality. Be sure to quantify the results of your optimizations.

Identify common challenges like data silos or regulatory changes. Discuss proactive strategies to address these, such as improving communication and knowledge sharing across departments or staying updated on regulatory developments.

Share your strategies for staying informed about the latest trends in data governance, such as participating in webinars, attending conferences, or being part of professional groups. Show how continuous learning has positively impacted your professional growth.

Discuss your hands-on experience with data warehousing solutions, outlining specific platforms you've worked with and how you've contributed to their structuring, security, or optimization for better data accessibility.

Provide a clear definition of data lineage and explain how it helps organizations track data flow, enhances data quality, and ensures compliance. Use examples from your experience to illustrate its application in governance.

Discuss your systematic approach to crafting data governance policies. Outline steps from stakeholder engagement to drafting and implementing policies, emphasizing the importance of alignment with organizational goals and regulatory standards.