L

Lazard

Advises on corporate deals and manages investments

Enterprise Data Product Manager - Operations

Technical Product ManagementConfirmed live in the last 24 hours
Full-timeNew York, NY, USAIn-person

About the Job

Requirements

  • At least 10 years in investment operations or investment data management, including at least 3 years accountable for data governance, data quality, or data products in a business-facing role.
  • A track record governing holdings, accounting, or AUM data across multiple asset classes at an asset manager or comparable regulated financial services business.
  • Deep knowledge of the investment data lifecycle, book of record concepts (IBOR and ABOR), and the realities of an outsourced middle and back office model.
  • Strong SQL skills and confidence working directly with data in a cloud warehouse or lakehouse, validating results independently.
  • Working knowledge of medallion architecture and data product concepts, and experience partnering with data engineering as the business owner.
  • Experience writing governance artifacts and leading through data owners outside the reporting line by influence rather than authority.
  • Experience working across a global organization with teams in multiple regions and time zones.
  • Credibility with senior investment and operations stakeholders.
  • An undergraduate degree or higher in a relevant field.

Responsibilities

  • 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; support them in running their products against published data contracts covering definitions, quality rules, refresh service-level agreements, and ownership.
  • Define data states (preliminary, final, restated) and 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.
  • 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 and report on quality controls operated by product owners across the domain, and steward 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 sales and distribution data domain to align definitions; support Finance as owner of AUM and flows; and retire shadow data sets in favor of governed products.
  • Own the logical design of the domain and its medallion structure, from raw provider ingestion through conformed layers to certified products, retaining 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.
  • Make the domain AI-ready by design, with semantic definitions, lineage, and entitlements supporting agentic workflows such as break investigation, pricing and NAV review, and self-service operational queries.
  • Make the domain business-ready so holdings, NAV, and AUM data are produced once and consumed across client reporting, factsheets, RFPs, CRM, finance reporting, and leadership dashboards.
  • Report progress to business and technology leadership against a roadmap, measured by governed products delivered, data quality metrics, adoption, and displacement of manual processes.

Desired Qualifications

  • Familiarity with State Street Alpha.
  • Experience with Snowflake, Databricks, or dbt, and catalog tooling such as Collibra or Unity Catalog.
  • Experience delivering data for AI or agentic systems, including semantic definitions and entitlements for machine consumers.
  • Experience with private assets data, or with master data programs for security, portfolio, or account masters.
  • Relevant certifications such as CDMP or cloud data platform certifications.

About the Company

Lazard

Advises on corporate deals and manages investments

Lazard advises companies and governments on major financial decisions and manages investment portfolios for institutions, families, and wealthy individuals. Its financial advisory teams work on mergers, capital raising, and debt restructurings, combining industry knowledge with local teams that coordinate across markets. The asset management business researches investments and runs portfolios across stocks, bonds, and alternative assets, while specialized advisers analyze geopolitical risks for corporate leaders. Lazard earns fees for advisory assignments and investment management, with investment fees generally tied to client assets. The firm traces its roots to 1848 and is headquartered in New York City.

Company size
1,001-5,000
Company stage
IPO
Headquarters
New York, NY
Founded
1848

Recently Posted Jobs

Explore more opportunities at Lazard

See more jobs