Senior Business Lead, Data Governance Strategy & Execution

Freddie Mac•McLean, VA

About The Position

The Multifamily Data organization is seeking a Senior Business Lead, Data Governance Strategy & Execution to help shape and execute the future of data governance across Multifamily. As Multifamily expands self-service access to data and enables new analytics, automation, and AI capabilities, trusted and well-governed data has become a strategic business imperative. This role will lead efforts to evolve governance from manual processes and one-time reviews into scalable capabilities embedded within our data platform, data products, and delivery processes. Working across business, technology, risk, privacy, compliance, and data teams, this leader will drive the strategy and execution needed to ensure Multifamily data is trusted, transparent, reusable, and fit for purpose. The role will also help establish the governance foundations necessary to support responsible AI adoption and ensure alignment between data governance and emerging AI governance requirements. Multifamily Data is transforming how data is managed, delivered, understood, and consumed across the business. Our mission is to provide a trusted data foundation that enables better business decisions, operational efficiency, regulatory compliance, advanced analytics, and AI-driven innovation. Through modern data platforms, trusted data products, and strong governance practices, we are improving transparency, strengthening data quality, and making data easier to discover, understand, and use. As Multifamily continues its data modernization journey, governance must evolve alongside the platform to ensure trust scales with growing volumes of data, consumers, analytics, and AI solutions.

Requirements

Bachelor's degree plus relevant experience.
10+ years of experience in Data Governance, Data Management, Data Strategy, Data Quality, Data Risk Management, or a related discipline.
Proven success leading large-scale, cross-functional initiatives through influence and collaboration.
Strong understanding of data governance frameworks, metadata management, data lineage, data quality, stewardship, and data controls.
Understanding of the relationship between data governance, AI governance, privacy, security, and responsible AI.
Experience with metadata, data catalog, lineage, and data quality platforms.
Experience with modern cloud data platforms, data products, and self-service analytics environments.
Experience translating business, regulatory, and technology requirements into practical governance solutions.
Experience collaborating across business, technology, risk, compliance, and data organizations.
Strong executive communication, presentation, and stakeholder management skills.
Ability to balance strategic thinking with hands-on execution.

Nice To Haves

Experience supporting advanced analytics, machine learning, or AI-enabled business solutions.
Experience within financial services or another highly regulated industry.
Advanced degree or relevant industry certifications.

Responsibilities

Define and advance Multifamily's data governance strategy, roadmap, and operating model.
Lead cross-functional initiatives that improve data quality, metadata management, data lineage, stewardship, ownership, and consumer trust.
Partner with Data Product, Engineering, Architecture, and Platform teams to embed governance directly into the data lifecycle.
Drive automation of governance capabilities, reducing reliance on manual oversight while increasing consistency and transparency.
Establish scalable governance capabilities that support trusted self-service reporting, analytics, and data product consumption.
Define and implement the data governance foundations needed to support responsible and effective AI adoption.
Serve as a key connector between data governance and AI governance, ensuring appropriate controls, lineage, transparency, privacy, accountability, and data readiness standards are in place.
Partner with Risk, Privacy, Compliance, Audit, and Regulatory stakeholders to ensure governance practices align with enterprise and regulatory expectations.
Develop meaningful metrics that demonstrate improvements in data trust, governance maturity, consumer adoption, and AI readiness.
Influence senior leaders and stakeholders to drive alignment and execution without direct authority.