Data Governance Analyst

Live Nation Entertainment•Beverly Hills, CA

1d•$137,500 - $144,000•Hybrid

About The Position

Live Nation Worldwide, Inc. is seeking a Data Governance Analyst to implement and maintain Data Governance frameworks, policies, and procedures aligned with the company’s Data Strategy. The role delivers governance activities across assigned data domains, supports compliance and oversight, and monitors the effectiveness and maturity of the Data Governance program. The analyst maintains enterprise metadata repositories, including data dictionaries, tags, and lineage documentation; monitors metadata quality; identifies and governs critical data elements (CDEs); and develops data standards, naming conventions, and validation rules. The position partners with Data Engineering on quality checks in ETL/ELT pipelines, data profiling, root-cause analysis, and remediation of quality issues and modeling gaps. The role uses cloud and AI technologies to develop multi-agent architectures that generate data dictionaries by analyzing Confluence, GitLab, YAML pipelines, and Unity Catalog. It evaluates AI-generated metadata with subject-matter experts, develops prompt-engineering strategies, optimizes agent workflows, monitors AI-assisted processes, documents AI governance practices, and researches emerging AI/ML technologies. The analyst collaborates with Data Engineering, Analytics, Platform, Legal, Compliance, and Security teams; facilitates working groups and domain forums; provides training and consulting; and supports data classification, sensitivity labeling, access controls, data handling procedures, retention policies, and escalation of potential privacy risks. The role tracks governance metrics and prepares dashboards, reports, and KPI insights; researches and evaluates governance tools and industry practices; and develops and maintains governance procedures, workflows, glossaries, knowledge-base articles, FAQs, policies, technical guides, and wiki documentation. Telecommuting is permitted pursuant to company policy. The position is based in Beverly Hills, California.

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.
Experience with data catalog tools such as Collibra or Informatica CDGC.
Experience with 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 including CCPA and GDPR, and privacy compliance implementation.
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.
Skills may be gained through academic coursework and concurrently while pursuing academic studies.

Responsibilities

Implement and maintain Data Governance frameworks, policies, and procedures aligned with the company’s Data Strategy.
Deliver governance activities across assigned data domains and participate in committee meetings.
Conduct impact assessments for proposed changes to data structures, policies, and processes, and monitor the effectiveness and maturity of the Data Governance program.
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 quality issues and modeling gaps.
Use cloud and AI technologies to build multi-agent architectures that generate automated data dictionaries from Confluence, GitLab, YAML pipelines, and Unity Catalog.
Evaluate and refine AI-generated metadata with subject-matter experts, develop prompt-engineering strategies, optimize agent workflows, and monitor AI-assisted processes.
Document AI governance processes, agent configurations, and best practices, and research emerging AI/ML technologies for governance.
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; advocate for data management best practices.
Develop user-friendly documentation, self-service resources, and training materials.
Support data classification, sensitivity labeling, and access control initiatives; document data handling procedures and retention policies; and escalate potential privacy risks.
Track and report governance metrics, including metadata completeness, data quality scores, standard adoption, and CDE coverage; prepare dashboards, status reports, and KPI insights.
Research governance technologies, methodologies, and industry trends; stay current on metadata management, data quality, data discovery, and AI-enabled governance.
Identify process-improvement opportunities through automation and tool optimization; evaluate new tools and platforms, including proof-of-concept assessments.
Benchmark organizational practices against industry standards and maturity models.
Develop and maintain governance procedures, workflows, data glossaries, business terms, knowledge-base articles, FAQs, and policy documents.
Prepare technical guides, maintain version control for governance documentation, contribute to the enterprise data governance wiki, and document governance decisions and architectural patterns.