Data Governance Analyst

Live Nation Entertainment•Beverly Hills, CA

About The Position

The Data Governance Analyst will implement and maintain Data Governance frameworks, policies, and procedures aligned with the company’s Data Strategy, delivering governance activities across assigned data domains. The role creates and maintains enterprise metadata repositories and quality standards, identifies and governs critical data elements, develops data standards and validation rules, and partners with Data Engineering to embed quality checks in ETL/ELT pipelines. It also conducts profiling and root-cause analysis, tracks remediation, and monitors governance program effectiveness and maturity. The analyst will use cloud and AI technologies to build multi-agent architectures that generate data dictionaries from sources such as Confluence, GitLab, YAML pipelines, and Unity Catalog. The role evaluates AI-generated metadata with subject-matter experts, develops prompt-engineering strategies, refines agent workflows, documents AI governance practices, and monitors these processes. The analyst collaborates with Data Engineering, Analytics, Platform, Legal, Compliance, and Security teams; facilitates working groups; supports classification, sensitivity labeling, access controls, retention, and privacy-risk escalation; and provides training and consulting support. The position tracks governance metrics and prepares dashboards, status reports, and KPI insights. It researches and evaluates governance technologies, conducts proof-of-concept assessments, benchmarks practices against industry standards and maturity models, and identifies automation opportunities. The role also develops and maintains governance procedures, workflows, glossaries, business terms, knowledge-base articles, FAQs, policy documents, technical guides, and wiki content. Telecommuting is permitted pursuant to company policy.

Requirements

Master’s degree or foreign equivalent in Computer Science or a related quantitative field.
At least 3 years of experience as a Data Analyst, Data Quality Manager, or in a related occupation.
Experience with SQL and navigating data warehouses.
Experience with Python, data analysis, data catalogs (Collibra or Informatica CDGC), and data mining.
Experience with BI platforms, including Microsoft Power BI, Oracle BI, and Tableau.
Experience with Databricks and Unity Catalog.
Experience developing and implementing predictive analytics models, including logistic regression, to analyze and interpret complex datasets.
Experience analyzing structured and time-series data to identify patterns and generate predictive insights.
Experience with a version control system, specifically GitLab.
Experience with privacy laws and compliance implementation, including CCPA and GDPR.
Experience with the end-to-end data supply chain from production to consumption.
Experience training teams and rolling out new programs across multiple business units.

Responsibilities

Implement and maintain Data Governance frameworks, policies, and procedures aligned with company Data Strategy.
Deliver governance activities across assigned data domains and participate in governance committee meetings.
Conduct impact assessments for proposed changes to data structures, policies, and processes; monitor program effectiveness and governance maturity.
Create and maintain enterprise metadata repositories, including data dictionaries, tags, and data lineage documentation.
Monitor metadata quality and identify, classify, and maintain critical data elements 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 and root-cause analysis, and track remediation of data quality issues and modeling gaps.
Build AI-assisted, multi-agent architectures to generate data dictionaries by analyzing Confluence, GitLab, YAML pipelines, and Unity Catalog.
Evaluate and refine AI-generated metadata with subject-matter experts; develop prompt-engineering strategies and optimize agent workflows.
Monitor AI-assisted governance processes, research emerging AI/ML technologies, and document AI governance processes, agent configurations, and best practices.
Partner with Data Engineering, Analytics, Platform, Legal, Compliance, and Security teams to improve governance and support regulatory compliance.
Facilitate data governance working groups and domain-specific forums.
Provide training, onboarding, guidance, consulting support, and timely responses to governance inquiries; create self-service resources and training materials.
Support data classification, sensitivity labeling, and access control initiatives; document data handling and retention procedures and escalate potential privacy risks.
Track and report governance metrics, including metadata completeness, data quality scores, standard adoption, and critical data element coverage; prepare dashboards, status reports, and KPI insights.
Research governance technologies, methodologies, and industry trends; evaluate tools and platforms, conduct proof-of-concept assessments, and benchmark practices against industry standards and maturity models.
Identify opportunities to improve governance processes through automation and tool optimization.
Develop and maintain governance documentation, including procedures, workflows, data glossaries, business terms, knowledge-base articles, FAQs, and policy documents; prepare technical guides and maintain version control.
Contribute to the enterprise data governance wiki and document governance decisions and architectural patterns.