Director of Data Strategy & Governance - Private Credit​/Equity – Greenwich CT

Director of Data Strategy & Governance

Private Credit/Equity - Greenwich CT

J Harlan Group is currently conducting a search for a strategic, hands-on leader to serve as their first Head of Data Strategy & Governance. Director of Data Strategy & Governance at a prominent Greenwich CT Private Credit/Equity organization.

The Director of Data Strategy & Governance will be a significant contributor to enabling the firm’s overall data vision and helping the organization to grow and improve their businesses.

This is a high-impact, newly created role that will define and own the firm's enterprise data program from the ground up. The successful candidate will partner closely with Investment, Finance, Risk, Compliance, and Technology teams to understand data needs, rationalize and document their data landscape, establish governance and quality standards, and ensure their data assets are structured, trusted, and AI-ready.

This role sits within the Strategic Initiatives organization and reports directly to the Managing Director, Strategic Initiatives, with a dotted line to the CTO for platform, tooling, and AI execution. It is a unique opportunity to shape how a sophisticated investment firm thinks about and operationalizes data as a strategic asset.

The firm views Data as a distinct commercial advantage - enabling a host of opportunities that differentiate them from their competitors.

The firm is a fast-growing and dynamic investment organization that is experiencing exceptional growth and is looking for exceptional people to power its next phase of growth.

Principal Responsibilities:

Data Strategy & Roadmap

• Define and own the firm’s multi-year data strategy, aligning it with firm-wide investment and operational priorities.
• Develop and maintain a comprehensive data roadmap covering sources, platforms, integration patterns, and analytics capabilities.
• Serve as the internal thought leader and evangelist for data and AI readiness across the organization.

Data Inventory & Source Management

• Conduct a full audit and inventory of all internal and third-party data sources (e.g., Deal Cloud, Databricks, Bloomberg, Octus, Green Street, Yardi, and partner-owned platforms such as Snowflake environments).
• Document data lineage, ownership, refresh cadences, formats, and access patterns for each source.
• Partner with vendors and internal teams to expand and rationalize the data estate as business needs evolve.

Data Governance

• Design and implement a formal data governance framework, including policies, standards, roles, and accountability structures.
• Establish a data stewardship model across key business domains:
  Entity, People, Security/Instrument, Investment Opportunity, Commitment & Capital, Transaction, and Position/Holding.
• Define and enforce data classification, retention, access control, and privacy policies in coordination with Legal and Compliance.
• Chair or co-chair a Data Governance Committee with cross-functional representation.

Data Dictionary & Data Modeling

• Build and maintain a firm-wide business glossary and data dictionary, defining authoritative definitions for all key data entities and metrics.
• Design and document canonical data models across the firm's seven core data domains.
• Establish naming conventions, attribute standards, and entity relationships to enable consistent downstream consumption.

Data Quality

• Define data quality dimensions (completeness, accuracy, consistency, timeliness) and implement monitoring and alerting.
• Partner with engineering and analytics teams to embed data quality checks into ingestion pipelines and transformation layers.
• Establish SLAs for critical data assets and track remediation of quality issues.

AI Readiness

• Lead the effort to make the firm's data estate AI-ready—structured, labeled, governed, and accessible for LLM and ML workloads.
• Partner with the CTO and technology team on Databricks Genie Spaces, natural language query interfaces, and the firm’s AI Bot initiative.
• Identify and remediate gaps in data structure, documentation, and coverage that limit AI use cases.
• Work with AI Committee members to prioritize high-value data and AI opportunities across investment and operational workflows.

Stakeho…