Head of Data Governance

Lazard•United States,

4d•$200,000 - $275,000•Hybrid

About The Position

Lazard is seeking an exceptional Head of Data Governance to serve as the firm’s authority on enterprise data governance. Reporting to the Head of AI and Data, you will architect and lead a firmwide governance framework that treats data as a trusted, well-governed strategic asset across Lazard’s Financial Advisory and Asset Management businesses. This is a hands-on leadership role requiring deep technical fluency, proven experience operating across multiple lines of business in a regulated financial services environment, and the credibility to drive enterprise-wide accountability at the most senior levels. The ideal candidate has served as a head of data governance, or equivalent, at a bank, asset manager, broker-dealer, or similarly complex financial institution, and brings a track record of designing and enforcing enterprise controls, security controls, and technical data architecture across diverse business lines with differing data needs, regulatory profiles, and risk tolerances.

Requirements

12+ years of experience in data governance, data management, or related disciplines in financial services, with at least 5 years in a senior leadership capacity (e.g., Head of Data Governance, Chief Data Officer, VP/MD-level data governance lead)
Proven track record operating at a financial services firm with multiple lines of business (e.g., investment banking, asset management, lending, trading, or insurance), with direct experience navigating different data domains, regulatory regimes, and business unit priorities
Deep expertise in enterprise data governance frameworks, methodologies, and operating models (e.g., DCAM, DAMA-DMBOK, or equivalent) including hands-on design and implementation experience, not just advisory oversight
Direct experience designing and enforcing enterprise controls and data security controls, including access governance, data classification, sensitive data management, and integration with information security frameworks
Demonstrated technical depth: ability to engage credibly with data engineers, architects, and platform teams on data modeling, pipeline design, cloud data infrastructure, and governance tooling
Hands-on experience with data governance and data quality tooling
Familiarity with cloud data platforms (AWS, Azure, or GCP) and modern data stack architecture (data lakehouses, medallion architecture, data mesh, or similar)
Strong working knowledge of relevant financial services regulatory requirements: SEC, FINRA, GDPR, CCPA, BCBS 239, and data-related expectations from prudential regulators
Experience supporting or leading responses to internal audit, regulatory exams, and third-party reviews as a control owner
Undergraduate degree or higher in Computer Science, Engineering, Data Science, Mathematics, or a quantitative technical field

Nice To Haves

Experience governing data for AI and machine learning systems, including model data lineage, training data governance, and AI risk frameworks
Background in quantitative finance, financial data models, or securities data (market data, reference data, portfolio data)
Relevant certifications: CDMP, CIPPE, CISM, or equivalent
Experience at a global firm with cross-border data flows and multi-jurisdictional regulatory obligations

Responsibilities

Define and own the firmwide data governance strategy — policies, standards, operating models, and accountability structures — across Financial Advisory and Asset Management lines of business
Architect and enforce enterprise-grade data controls spanning data quality, access, lineage, lifecycle management, and classification, with clear escalation paths and issue remediation workflows
Establish data ownership and stewardship accountability at the business line and function level, with governance structures that scale across a multi-LOB organization
Design and operate a governance operating model that integrates with first- and second-line risk frameworks, including three-lines-of-defense alignment
Provide regular reporting to senior management and the Board (as appropriate) on data quality metrics, governance effectiveness, open issues, and remediation status
Lead the design of the firm’s enterprise data architecture governance layer — covering data platform standards, canonical data models, metadata management, data lineage, and master data management
Actively engage in technical design reviews for data infrastructure, AI/ML pipelines, and analytics platforms to ensure governance is embedded at the architectural level, not bolted on after the fact
Define and enforce data classification schemes, sensitivity labeling, and data handling standards that are operationally grounded and technically implementable
Partner with Data Engineering and Platform Engineering to embed governance controls within data pipelines, data lakes, warehouses, and cloud infrastructure (AWS, Azure, or GCP)
Evaluate and own the firm’s data governance toolchain — including data catalogs, data quality engines, lineage tools, and observability platforms — with hands-on involvement in selection, configuration, and adoption
Partner with Information Security to define and enforce data security controls, including role-based and attribute-based access, data masking, tokenization, and encryption standards across data environments
Own the governance of sensitive and regulated data categories — including client data, MNPI, personally identifiable information, and proprietary financial data — ensuring controls meet regulatory and internal policy requirements
Ensure data governance practices support regulatory reporting obligations, auditability, records retention, and supervisory expectations across relevant jurisdictions (SEC, FINRA, GDPR, CCPA, and others as applicable)
Act as a key control owner in technology and operational risk frameworks; support internal audit, regulatory examinations, and external reviews with clear, auditable evidence of governance discipline
Collaborate with Legal, Compliance, and Privacy teams to keep governance standards current with evolving regulatory requirements and enforcement trends
Build, mentor, and lead a high-performing data governance and stewardship organization; attract and develop talent with both technical depth and business acumen
Serve as the firm’s senior voice on data governance with C-suite, business line heads, and the Board — translating complex data risk into clear business and strategic terms
Drive cross-LOB adoption of governance standards through influence, education, and accountability mechanisms rather than mandates alone
Establish governance communities of practice across business units to embed data stewardship into day-to-day operations