Data Product Management Jobs

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Vice President, Data Product Owner

BlackRock Investments New York, NY

New York, NY

Today

$163k - $215k/yr Full time Data Analysis Data Analytics Data Architecture

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Job Description

BlackRock’s Cross-Functional Technology (XFT) team is seeking a Vice President, Data Product Owner to lead a portfolio of data products that support corporate functions. This role takes products from early discovery and definition through delivery, adoption, measurement, and continued lifecycle evolution, translating stakeholder needs into reusable and governed data capabilities.

Role Responsibilities

Own assigned domain data products from discovery through roadmap, requirements, delivery, adoption, measurement, and lifecycle management
Represent product plans through Agile execution, driving key decisions, managing dependencies, guiding prioritization, and seeing initiatives through to completion
Lead product discovery and requirements analysis, assessing business value, cost, dependencies, and competing priorities to recommend sequencing and tradeoffs
Partner with business stakeholders to define product outcomes, data definitions, service expectations, and measures of success
Design and evolve domain data models, including core business concepts, relationships, reference or master data, and reusable data structures
Coordinate with data engineering, platform, BI and reporting, and architecture teams on pipelines, transformations, access patterns, entitlements, analytical consumption, and distribution mechanisms
Provide product direction and day-to-day leadership for small analyst teams

Required Qualifications

8+ years of relevant experience in enterprise data, data products, product management, data architecture and modeling, data governance or stewardship, or related disciplines
Proven experience owning or leading data products across the full product lifecycle
Strong understanding of enterprise data fundamentals, including data definitions, data quality, lineage, metadata, ownership, and governance
Hands-on experience with relational and normalized data modeling and dimensional data modeling, with the ability to collaborate effectively with business stakeholders, architects, and engineers
Demonstrated ability to operate independently and drive outcomes in a complex, matrixed enterprise environment
Experience in at least one relevant corporate data domain, such as finance, treasury, tax, HR, client or revenue, legal and compliance, regulatory reporting, procurement, or enterprise master or reference data

Preferred (Nice-to-Have) Experience

Deep experience in data product practices, including implementation or evolution of product development lifecycle processes, discovery, roadmap and backlog practices, prioritization, PI planning, and metrics
Expertise in enterprise data modeling, including semantic or domain modeling, canonical concepts, master or reference data, normalization, dimensional models, and modeling standards
Experience with Oracle Financials, SAP, TM1 or Planning Analytics, Salesforce, Workday, Microsoft Dynamics, or Coupa
Familiarity with cloud data platforms, BI or analytics platforms, metadata or catalog solutions, and data-quality tooling
Experience in asset management, financial services, or a similar industry

Compensation

USD 162,500 - 215,000 per year

Benefits

Annual discretionary bonus
Healthcare
Leave benefits
Retirement benefits, including a strong retirement plan
Tuition reimbursement
Support for working parents
Flexible Time Off (FTO)

Additional Benefits (Company Summary)

Strong retirement plan
Tuition reimbursement
Comprehensive healthcare
Support for working parents
Flexible Time Off (FTO)

Hybrid Work Model

Employees are required to work at least 4 days in the office per week
Flexibility to work from home 1 day a week
Some business groups may require more time in the office depending on role and responsibilities

Location

New York, New York and Princeton, NJ

AI Use Guidance for Candidates

Candidates are encouraged to use AI thoughtfully to learn, prepare, and work more effectively
During the interview process, the focus is on learning from candidates’ own experiences, thinking, and judgment

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