Data Governance Analyst

Live Nation Entertainment Inc; Beverly Hills (CA); On-site; USD 138,000 - 144,000; Full time

Benefits offered by this job

Telecommuting allowed

Job summary

Live Nation Worldwide, Inc. in Beverly Hills, CA seeks a Data Governance Analyst to implement and maintain governance frameworks aligned with the company Data Strategy. You will drive metadata repositories, data dictionaries, and data quality rules while partnering with engineering, analytics, and legal teams to ensure regulatory compliance.

The role covers AI-enabled governance, PMO-style reporting, and training resources; telecommuting is permitted per policy.

Qualifications

• Master’s degree or foreign equivalent in a quantitative field.
• 3+ years of experience in data analysis, quality, or related roles.
• Experience implementing data governance, metadata management, and AI-enabled governance.

Responsibilities

• Implement and maintain Data Governance frameworks and policies.
• Create and maintain enterprise metadata repositories and data dictionaries.
• Monitor metadata quality and data governance metrics across domains.
• Collaborate with Data Engineering, Analytics, Platform, Legal, Compliance, and Security teams.
• Develop AI governance processes and document agent configurations.

Skills

SQL

Python data analysis

Data mining

BI platforms

Databricks

Unity Catalog

Gitlab

Privacy laws (CCPA, GDPR)

End-to-end data supply chain

Education

Master’s degree in Computer Science or related quantitative field

Tools

Collibra

Informatica CDGC

Data catalogs

Job description

Job Summary

Data Governance Analyst (Live Nation Worldwide, Inc.; Beverly Hills, CA): Implement and maintain Data Governance frameworks (DAMA-DMBOK), policies, and procedures aligned with company Data Strategy. Deliver governance activities across assigned data domains ensuring consistency, oversight, and compliance. Participate in committee meetings, conduct impact assessments for proposed changes to data structures, policies and processes, and monitor the effectiveness of the Data Governance program to enhance the Governance maturity model. Create and maintain enterprise metadata repositories including data dictionaries, tags, and data lineage documentation. Monitor metadata quality standards ensuring accuracy and completeness across all data assets. Identify, classify, and maintain CDEs with appropriate governance controls. Develop and enforce Data Standards, naming conventions, and data quality validation rules. Partner with Data Engineering to integrate quality checks into ETL/ELT pipelines. Perform data profiling, root cause analysis, and track remediation of quality issues and modeling gaps. Use cloud and AI technologies to build multi-agent architectures that generate automated data dictionaries by analyzing Confluence, GitLab, YAML pipelines, and Unity Catalog. Evaluate and refine AI-generated metadata through SME collaboration ensuring accuracy and relevance. Develop prompt engineering strategies and optimize agent workflows for documentation quality. Monitor effectiveness of AI-assisted processes and research emerging AI/ML technologies for governance. Document AI governance processes, agent configurations, and best practices. Partner with Data Engineering, Analytics, Platform, Legal, Compliance, and Security teams to enhance governance processes and ensure regulatory compliance. Facilitate data governance working groups and domain-specific forums. Provide training, onboarding, and guidance on governance tools, standards, and processes. Develop user-friendly documentation, self-service resources, and training materials. Respond to governance inquiries within SLAs, provide consulting support, and advocate for data management best practices. Support data classification, sensitivity labeling, and access control initiatives. Document data handling procedures, retention policies, and escalat[e] potential privacy risks. Track and report governance metrics: metadata completeness, data quality scores, standard adoption, CDE coverage. Prepare dashboards, status reports, and KPI insights to demonstrate governance value. Research governance technologies, methodologies, and industry trends through conferences and professional networks. Research data governance technologies, methodologies, and industry trends through conferences, training, and professional networks. Stay current on advancements in metadata management, data quality, data discovery, and AI-enabled governance. Identify opportunities to improve governance processes through automation and tool optimization. Evaluate new tools and platforms for potential adoption, conducting proof-of-concept assessments. Benchmark organizational practices against industry standards and maturity models. Develop and maintain governance documentation: procedures, workflows, data glossaries, business terms, knowledge base articles, FAQs, and policy documents. Prepare technical guides and maintain version control for all governance documentation. Contribute to enterprise data governance wiki and document governance decisions and architectural patterns. Telecommuting permitted pursuant to company policy.

Job Summary

Data Governance Analyst (Live Nation Worldwide, Inc.; Beverly Hills, CA): Implement and maintain Data Governance frameworks (DAMA-DMBOK), policies, and procedures aligned with company Data Strategy. Deliver governance activities across assigned data domains ensuring consistency, oversight, and compliance. Participate in committee meetings, conduct impact assessments for proposed changes to data structures, policies and processes, and monitor the effectiveness of the Data Governance program to enhance the Governance maturity model. Create and maintain enterprise metadata repositories including data dictionaries, tags, and data lineage documentation. Monitor metadata quality standards ensuring accuracy and completeness across all data assets. Identify, classify, and maintain CDEs with appropriate governance controls. Develop and enforce Data Standards, naming conventions, and data quality validation rules. Partner with Data Engineering to integrate quality checks into ETL/ELT pipelines. Perform data profiling, root cause analysis, and track remediation of quality issues and modeling gaps. Use cloud and AI technologies to build multi-agent architectures that generate automated data dictionaries by analyzing Confluence, GitLab, YAML pipelines, and Unity Catalog. Evaluate and refine AI-generated metadata through SME collaboration ensuring accuracy and relevance. Develop prompt engineering strategies and optimize agent workflows for documentation quality. Monitor effectiveness of AI-assisted processes and research emerging AI/ML technologies for governance. Document AI governance processes, agent configurations, and best practices. Partner with Data Engineering, Analytics, Platform, Legal, Compliance, and Security teams to enhance governance processes and ensure regulatory compliance. Facilitate data governance working groups and domain-specific forums. Provide training, onboarding, and guidance on governance tools, standards, and processes. Develop user-friendly documentation, self-service resources, and training materials. Respond to governance inquiries within SLAs, provide consulting support, and advocate for data management best practices. Support data classification, sensitivity labeling, and access control initiatives. Document data handling procedures, retention policies, and escalat[e] potential privacy risks. Track and report governance metrics: metadata completeness, data quality scores, standard adoption, CDE coverage. Prepare dashboards, status reports, and KPI insights to demonstrate governance value. Research governance technologies, methodologies, and industry trends through conferences and professional networks. Research data governance technologies, methodologies, and industry trends through conferences, training, and professional networks. Stay current on advancements in metadata management, data quality, data discovery, and AI-enabled governance. Identify opportunities to improve governance processes through automation and tool optimization. Evaluate new tools and platforms for potential adoption, conducting proof-of-concept assessments. Benchmark organizational practices against industry standards and maturity models. Develop and maintain governance documentation: procedures, workflows, data glossaries, business terms, knowledge base articles, FAQs, and policy documents. Prepare technical guides and maintain version control for all governance documentation. Contribute to enterprise data governance wiki and document governance decisions and architectural patterns. Telecommuting permitted pursuant to company policy.

Minimum requirements

Master’s degree or foreign equivalent in Computer Science or related quantitative field, plus 3 year(s) of experience as a Data Analyst, Data Quality Manager, or related occupation.

Must Have Experience With The Following

• SQL and navigate data warehouses;
• Python Data Analysis
• Data Catalog (Collibra, Informatica CDGC)
• Data mining;
• BI platforms (Microsoft Power BI, Oracle BI, and Tableau);
• Databricks, Unity Catalog;
• Experience with developing and implementing predictive analytics models, including logistic regression, to analyze and interpret complex datasets;
• Analyzing structured and time-series data to identify patterns and generate predictive insights;
• Version Control System (Gitlab)
• Privacy laws (CCPA, GDPR, and Privacy Compliance implementation);
• End-to-end data supply chain from production to consumption; and
• Training teams and rolling out new programs across multiple business units.

Skills may be gained through academic coursework and concurrently while pursuing academic studies

Salary: $137,500.00 to $144,000.00 per year

An EOE.