Senior Data Modeler - Enterprise Data Domains & Architecture

Role: Senior Data Modeler Enterprise Data Domains & Architecture

Location: Remote

Duration: 3 6 months

Position Overview

We are seeking a highly experienced Senior Data Modeler / Data Architect with deep expertise in private equity, asset management, investment management, or alternative investments. This individual will play a critical role in defining how data is structured, governed, and utilized across the investment lifecycle. The ideal candidate is a hands-on data professional who can work directly with business leaders, investment professionals, finance teams, and portfolio operations stakeholders to understand complex business challenges and translate them into scalable enterprise data models and architectures. We are looking for someone who can independently analyze business problems, develop conceptual models, challenge assumptions, identify gaps, and design solutions that support both current and future business needs. The successful candidate will possess a strong foundation in Data Governance and Data Management that has evolved into expertise in Data Modeling and Enterprise Data Architecture. They must be able to get into the details, understand the data, model it, challenge assumptions, and translate business requirements into practical enterprise data structures.

Key Responsibilities

Enterprise Data Modeling

• Develop and maintain conceptual, logical, and physical data models across core private equity business domains.
• Translate complex investment, finance, and portfolio management requirements into scalable and maintainable enterprise data structures.
• Define entities, attributes, relationships, hierarchies, business rules, and data definitions.
• Create business-focused models that accurately represent real-world investment and operational processes.
• Identify opportunities to standardize data across investment, finance, and portfolio operations functions.
• Establish reusable enterprise data assets that support reporting, analytics, operational workflows, and future growth initiatives.

Data Domain Expertise

• Demonstrate deep, practical understanding of business data domains and how those domains interact.
• Define and document domain boundaries, critical data elements, relationships, and ownership.
• Work with business and technology stakeholders to establish a common understanding of domain data.
• Understand how data moves across systems and how changes in one domain impact other domains.
• Identify authoritative sources and establish appropriate ownership and stewardship for critical data.
• Explain complex data-domain concepts clearly to both technical and non-technical audiences.

Private Equity Domain Modeling

Develop and maintain enterprise data models across key private equity and investment management domains including:

• Funds
• Limited Partners (LPs)
• Investors
• Capital Calls
• Distributions
• Portfolio Companies
• Investments
• Ownership Structures
• Valuations
• Deal Pipelines
• Acquisitions & Exits
• Financial Performance
• Portfolio Operations
• Investment Committees
• Risk & Compliance
• Reference Data

Data Governance Data Architecture

• Leverage a strong foundation in Data Governance, Data Management, and Data Quality to drive effective data architecture.
• Connect governance policies and business definitions directly to enterprise data models.
• Apply knowledge of data ownership, stewardship, lineage, metadata, standards, and data quality to modeling decisions.
• Help mature the organization's data governance capabilities into practical enterprise data architecture and modeling practices.
• Establish and enforce modeling standards, naming conventions, definitions, and modeling patterns.

Data Architecture

• Contribute to and influence enterprise data architecture decisions.
• Develop domain-oriented data architectures that support analytics, operational systems, reporting, and emerging data initiatives.
• Support modernization initiatives involving cloud platforms, data warehouses, data lakes/lakehouses, APIs, and data products.
• Ensure data models align with broader enterprise architecture and technology strategies.
• Identify duplication, inconsistencies, and gaps across enterprise data landscapes.

Required Experience

• 8+ years of experience in Data Modeling, Data Architecture, Data Governance, or Data Management.
• Hands-on experience creating conceptual, logical, and physical data models.
• Experience working within Private Equity, Asset Management, Investment Management, Alternative Investments, Hedge Funds, Venture Capital, or Financial Services environments.
• Strong understanding of private equity business concepts, investment lifecycles, and associated data domains.
• Demonstrated ability to work directly with executives, investment professionals, finance leaders, and business stakeholders.
• Proven ability to translate loosely defined business requirements into well-structured enterprise data models.
• Strong understanding of Data Governance, Data Quality, Metadata Management, Data Lineage, and Data Stewardship.
• Experience defining business entities, ownership structures, relationships, and critical data elements.
• Strong SQL and relational database expertise.
• Experience with enterprise modeling tools such as ERwin, ER/Studio, Sparx Enterprise Architect, or equivalent.
• Exceptional communication skills with the ability to explain complex data concepts to both technical and non-technical audiences.