Role: Chief Data Officer / Senior Executive Leader (Private Equity)
Location: Remote
Duration: 3 - 6 months
Position Overview
We are seeking a senior data leader to serve as a key partner to the Director of Data Strategy & Management. This individual will function as the operational leader and strategic lieutenant for the firm's data organization, helping define, execute, and scale the enterprise data strategy across the private equity platform. The ideal candidate combines strong private equity domain knowledge, enterprise data expertise, and hands-on problem-solving capabilities. This person will play a critical role in establishing trusted data assets, improving business decision-making, and creating a scalable enterprise data foundation that supports investment operations, portfolio management, finance, investor relations, and future growth initiatives.
Key Responsibilities
Data Strategy & Execution
- Partner closely with the Director of Data Strategy & Management to execute the firm's enterprise data vision and roadmap.
- Serve as a trusted advisor and second-in-command for data strategy initiatives.
- Translate business priorities into practical data solutions, roadmaps, and architectural approaches.
- Drive delivery of enterprise data initiatives from concept through implementation.
- Identify opportunities to improve business processes through better data management, governance, and analytics.
Private Equity Data Leadership
Lead and improve data capabilities across key business domains including:
- Funds
- Limited Partners (LPs)
- Investors
- Portfolio Companies
- Investments
- Deal Pipeline
- Capital Calls
- Distributions
- Financial Reporting
- Valuations
- Performance Metrics
- Portfolio Operations
- Risk & Compliance
Responsibilities include:
- Defining business entities and relationships.
- Establishing common data definitions and standards.
- Identifying data ownership and stewardship.
- Mapping data flows across business functions and systems.
- Creating scalable data models supporting analytics and reporting.
Data Architecture & Modeling
- Develop conceptual, logical, and physical data models supporting enterprise initiatives.
- Establish domain-oriented data architectures.
- Align governance, ownership, and business definitions with technical implementation.
- Support integration of data across investment, finance, CRM, reporting, and portfolio management platforms.
- Identify opportunities to eliminate redundant data and improve consistency across systems.
Data Governance & Quality
- Establish and mature governance processes, stewardship models, and data standards.
- Define critical data elements and quality controls.
- Support metadata management, data lineage, and business glossary development.
- Improve trust, transparency, and consistency across enterprise data assets.
- Partner with technology and business teams to address data quality issues.
Leadership & Organizational Development
- Act as a senior leader within the Data Strategy & Management organization.
- Mentor data architects, data modelers, analysts, and governance team members.
- Help establish operating models, processes, and best practices.
- Represent the Director of Data Strategy & Management when necessary.
- Influence stakeholders across investment, finance, operations, and technology functions.
Required Experience
- 10-15+ years of experience in Data Architecture, Data Strategy, Data Modeling, Data Governance, or Enterprise Data Management.
- Experience within Private Equity, Asset Management, Investment Management, Alternative Investments, or Financial Services.
- Strong understanding of fund, investment, portfolio company, investor, and financial data.
- Demonstrated success translating business challenges into enterprise data solutions.
- Hands-on experience creating conceptual, logical, and physical data models.
- Strong understanding of data governance, stewardship, metadata, lineage, and data quality practices.
- Experience partnering directly with executive stakeholders and business leaders.
- Strong SQL and data analysis capabilities.
- Experience working across both business and technology organizations.
- Strong understanding of regulatory, risk, privacy, and compliance considerations related to financial data
- Bachelor's degree required, advanced degree in Business, Finance, Computer Science, Data Science, Engineering, or a related field preferred.