Enterprise Data Product Manager - Operations at Lazard in New York, NY

Job description

Many of the world’s leading investors – from individuals to institutions across the globe – have entrusted us with approximately $280 billion in assets and rely on us to provide world-class investment solutions and advice. We pride ourselves on being at the forefront of complex financial markets, uncovering the best investment opportunities to deliver long-term value for our clients. Lazard Asset Management is seeking a Senior Vice President, Enterprise Data Product Manager, within the AI and Data Transformation team, to steward the investment operations data domain across multiple regions. The domain covers holdings, transactions, valuation and NAV, and AUM data across equities, fixed income, derivatives, and FX, with potential expansion into private assets, produced largely by our outsourced middle and back office provider. Day-to-day ownership sits with our Operations and Accounting teams; this role provides the oversight, governance, and architecture that make the data trusted, business-ready, and AI-ready across the firm. LAM is a GIPS-compliant firm. The ideal candidate has governed investment operations data at an asset manager, asset servicer, or comparable financial services business, understands the data model well enough to challenge how a provider produces it, and knows where breaks originate between front, middle, and back office. You lead through data product owners rather than around them, and you work fluently with data engineering without being an engineer or an operations processor. We’ll trust you with: Domain Stewardship & Data Governance Act as data steward and governance lead for the investment operations domain, setting data definitions, business rules, classification, entitlements, and retention for accounts, products, holdings, transactions, valuation, and NAV data, and representing the domain at the firm’s data governance forum Recommend data product owners and, in collaboration with Operations and Accounting team leads, agree their appointment, then support them in running their products against published data contracts covering definitions, quality rules, refresh SLAs, and ownership Define the data states (preliminary, final, restated) and the certification rules for when data is fit for internal, client, regulatory, or public use, and uphold the principle that a product without a contract is not available for consumption Domain Model & Data Product Oversight Define the domain model and its data products, including reference data, holdings, transactions, valuation and NAV, and AUM and flows, with boundaries, grain, and relationships agreed with their owners Oversee the quality controls that product owners operate and report on them across the domain, and steward the portfolio, account, and security cross-references so every holding joins cleanly across front, middle, and back office Partner with Operations, Accounting, Performance, Finance, Client Reporting, Risk, Compliance, and the sales and distribution data domain to align definitions, supporting Finance as owner of AUM and flows, and retire shadow data sets in favor of governed products Architecture & Delivery with Data Engineering Own the logical design of the domain and its medallion structure, from raw provider ingestion through conformed layers to certified products, with full history so official figures are never overwritten Translate business requirements into engineering specifications and hold the acceptance decision on whether a delivered product meets its contract, sequencing delivery as vertical slices by business and control value Define consumption paths for the domain, including governed APIs, a semantic layer with certified metrics, BI access, and interfaces for AI agents, with lineage and observability monitored in production AI & Business Readiness Make the domain AI-ready by design, with semantic definitions, lineage, and entitlements that support agentic workflows such as break investigation, pricing and NAV review, and self-