Data Governance Manager

Since 1973, East West Bank has served as a pathway to success. With over 110 locations across the U.S. and Asia, we are the premier financial bridge between the East and West. Our teams of experienced, multi-cultural professionals help guide businesses and community members on both sides of the Pacific looking to explore new markets and create new opportunities, and our sustained growth and expertise in industries like real estate, entertainment and media, private equity and venture capital, and high-tech help build sustainable businesses and expand our associates’ potential for career advancement.

Headquartered in California, East West Bank (Nasdaq: EWBC) is a top-performing commercial bank with a strong foundation, an enterprising spirit and a commitment to absolute integrity. East West Bank gives people the confidence to reach further.

East West Bank is seeking an experienced Data Governance to help develop, operationalize, and mature the bank’s enterprise data governance program. This role will establish governance standards, improve data quality and transparency, and enable trusted, compliant, and well-managed data across the organization.

The position is part of the Enterprise AI Strategy & Transformation team, focused on scaling AI use cases, pilots, and proofs of concept into governed, measurable, and enterprise-ready capabilities.

This role partners closely with business stakeholders, data owners, technology teams, analytics teams, and risk and compliance functions to implement governance processes, metadata management, data stewardship frameworks, and enterprise controls supporting the bank’s broader data and AI strategy.

The ideal candidate is a hands-on governance practitioner with experience in regulated industries who can balance policy, process, and operational execution while driving enterprise-wide data maturity initiatives.

Key Responsibilities

• Support the implementation and ongoing maturation of the enterprise data governance framework, including policies, standards, procedures, and operating models.
• Partner with business and technology stakeholders to identify and document Critical Data Elements (CDEs), data ownership and stewardship assignments, business glossaries, data definitions, lineage, and data flows.
• Facilitate governance working sessions with business and technology teams to align on standards, remediation priorities, and governance objectives.
• Support enterprise metadata management, data cataloging, and lineage documentation using tools such as Microsoft Purview, Collibra, Alation, or Informatica.
• Assist with enterprise data quality management processes, including quality rules, controls, issue remediation, root-cause analysis, scorecards, and KPI reporting.
• Collaborate with data engineering, analytics, and architecture teams to embed governance controls within enterprise data pipelines and analytical platforms.
• Support governance activities related to data classification, sensitive data handling, access governance, retention, lifecycle management, and audit requirements.
• Develop and maintain governance artifacts including business glossaries, data dictionaries, stewardship matrices, operating procedures, and standards.
• Prepare governance reporting materials and metrics for governance councils, leadership reviews, and regulatory or audit activities.
• Promote data literacy and governance best practices across the organization.
• Support governance enablement within Azure-based environments including Azure Data Lake, Azure Databricks, Microsoft Fabric, and Power BI ecosystems.

Required AI & Data Governance Experience

• Hands-on experience applying governance controls to AI-enabled solutions, including data quality, lineage, ownership, access controls, retention, consent, and auditability.
• Experience governing AI use cases from intake through production, including risk assessment, approval workflows, monitoring, and issue remediation.
• Practical experience governing data used in LLM and RAG solutions, including source validation, sensitive data handling, ingestion controls, metadata management, and knowledge-base quality.
• Strong understanding of AI risk, model risk, data privacy, explainability, human oversight, and responsible AI practices in regulated environments.
• Ability to translate governance policies into repeatable operational procedures, controls, evidence requirements, metrics, and executive reporting.

AI Fluency & Hands-On LLM Experience

• Practical experience with major LLM platforms including OpenAI, Anthropic Claude, Microsoft Copilot/Azure OpenAI, Google Gemini, AWS Bedrock, and open-source models such as Llama or Mistral.
• Familiarity with prompt engineering, embeddings, vector search, RAG, agentic workflows, model evaluation, hallucination mitigation, and human-in-the-loop review.
• Ability to assess AI solutions for privacy exposure, explainability, monitoring requirements, production readiness, and governance risks.
• Experience partnering with technology, risk, compliance, legal, and business teams to govern AI responsibly while enabling innovation.

Required Technologies & Tooling

• Data governance and catalog platforms such as Microsoft Purview, Collibra, Alation, or Informatica.
• Cloud data platforms and lakehouse architectures including Snowflake, Databricks, Azure, AWS, or GCP.
• Data pipeline and orchestration tools such as dbt, Airflow, Azure Data Factory, AWS Glue, and Kafka.
• AI/ML lifecycle and monitoring tools including MLflow, model registries, evaluation frameworks, observability tools, and LLM monitoring platforms.
• Vector databases and AI infrastructure platforms such as Pinecone, Weaviate, FAISS, pgvector, and Azure AI Search.
• Security controls including IAM, encryption, DLP, tokenization/masking, secrets management, and audit logging.

Required Qualifications

• Bachelor’s degree in Information Systems, Data Management, Computer Science, Business Analytics, or a related discipline.
• 8 years of experience in data governance, AI governance, metadata management, data quality, data risk, or related enterprise data roles.
• Strong understanding of data governance concepts including stewardship, metadata management, lineage, data quality, and business glossaries.
• Experience supporting enterprise governance programs using tools such as Microsoft Purview, Collibra, Alation, or Informatica.
• Familiarity with modern cloud-based data ecosystems, particularly Azure-centric environments.
• Foundational SQL knowledge and experience working with structured data and relational databases.
• Understanding of banking regulatory and compliance considerations related to data governance and risk management.
• Strong analytical, organizational, communication, and stakeholder management skills.
• Experience leading cross-functional governance initiatives with measurable outcomes and executive visibility.
• Ability to translate complex AI and data risks into practical business and control decisions.

Preferred Qualifications

• Master’s degree or PhD in a quantitative discipline.
• Experience within commercial banking, regulatory reporting, AML/BSA, finance, risk management, or enterprise analytics.
• Familiarity with BCBS 239, SR 11-7, CCAR, CECL, and DAMA-DMBOK principles.
• Experience supporting enterprise data quality and remediation initiatives.
• Exposure to Azure Data Factory, Azure Databricks, Azure Synapse, and Microsoft Fabric.
• Experience supporting governance initiatives for AI/ML and advanced analytics environments.
• Professional certifications such as CDMP, DAMA, Microsoft Purview, or Collibra certifications.

Applicants must have legal authorization to work in the United States. We do not offer visa sponsorship at this time.

Compensation

The base pay range for this position is USD $120,000.00/Yr. - USD $200,000.00/Yr. Exact offers will be determined based on job-related knowledge, skills, experience, and location.