Senior Director - Single Family Acquisition Data Transformation

Freddie Mac•McLean, VA

6d•$225,000 - $337,000

About The Position

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview Freddie Mac is seeking a strategic and collaborative Senior Director to lead data modernization initiatives for the Single Family Acquisitions (SFA) division. This leader will serve as the primary liaison between E nterprise O perations & T echnology (EO&T) , Single Family Data, and SFA (data producers, data consumers, and data stakeholders) —ensuring partnership and alignment across all SFA data transformation efforts. The Senior Director will drive current and future data modernization initiatives within SFA—including the transition from legacy data platforms, adoption of business process-driven data models, and implementation of new, centralized, cloud-based data platforms —while leveraging data as a critical enabler to support innovation, operational efficiency, and business value for SFA. Our Impact: Leading Data Modernization for Single Family Acquisitions in partnership with EO&T and Single Family Data, we: Improve data quality, transparency, and efficiency across SFA and partner divisions Accelerate access to reliable information as SFA systems modernize Help retire legacy platforms, reducing risk and legacy maintenance for SFA Support the use of SFA data as a strategic enabler for business transformation and innovation—including advanced analytics and GenAI Support the create of cleaner, standardized Data Products that simplify analysis and decision-making for SFA

Requirements

15+ years of experience in data strategy, product/program management, or engineering, preferably in financial services or mortgage industry
Bachelor's degree in Computer Science , Information Systems, or related field; Master's d egree or MBA preferred
Strong background in data management , including acquisition, storage, governance, and security of data within an organization.
Experience with policies, procedures, and strategies to ensure data quality, accessibility, and compliance.
Experience with data modeling to support the design, structure, and organization of data for business and analytics purposes.
Experience in data science , including technical application and analysis of data to derive insights and drive decision-making.
Proficiency with advanced techniques such as statistics, machine learning, and artificial intelligence to process, analyze, and interpret data.
Proven track record delivering large, complex data transformation projects involving multiple teams and business units
Deep understanding of modern data platforms , data governance, and business process-driven data modeling
Experience with cloud-native data solutions, event-driven architectures, and enterprise data frameworks
Demonstrated ability to synthesize business and technical needs , deliver value, and drive adoption of new methodologies
Strong analytical, strategic, and problem-solving skills
Excellent written and verbal communication skills , including experience presenting to senior management
High comfort operating in ambiguity and managing multiple, concurrent assignments and competing priorities
Demonstrated leadership in product development, ownership, and change management
Acute business acumen and understanding of organizational issues and challenges
Track record of establishing and maintaining strong relationships across business and technology teams

Nice To Haves

Exceptional communication and stakeholder management skills - at all levels (product teams up to the executive team)
Organized, detail-oriented, and strategic thinker
Ability to transform complex SFA data modernization concepts—including leveraging SFA data as an enabler for innovation—into actionable plans
Ability to drive alignment and adoption across diverse SFA teams, including data producers and consumers
Strong leadership presence and influence at all levels of the SFA organization
Commitment to partnership and collaborative execution within SFA

Responsibilities

Lead SFA Data Modernization: Spearhead and champion data modernization efforts for the SFA division, including initiatives such as: Adopting the enterprise business model, a business process-driven approach to managing, defining, storing, and accessing SFA data across Freddie Mac. Retiring the legacy corporate data warehouse, a centralized relational database that consolidates disparate sources from transaction al processing / multiple systems to make historical and current SFA business-relevant data accessible. Migrating to a new centralized, cloud-based data platform serving as the single source of truth for SFA and enterprise data. Lea ding and support ing additional / new data modernization initiatives for SFA as they arise, ensuring data is leveraged as a foundational enabler for transformation—including, but not limited to, advanced analytics and GenAI (Generative AI) use cases.
Work Closely with SFA Data Producers and Consumers: Collaborate directly with both data producers and data consumers to ensure alignment, transparency, and shared understanding of requirements and deliverables.
Liaison Across Teams: Act as the primary bridge between EO&T, Single Family Data, and SFA (data producers, data consumers, and data stakeholders) — facilitating seamless communication, understanding, and collaboration to advance SFA data initiatives.
Program Execution: Drive the planning and delivery of SFA-specific data modernization roadmaps, coordinating with partner teams to ensure successful migration from legacy systems to modern, cloud-based data platforms and frameworks for SFA.
Champion Partnership: Foster a culture of collaboration, transparency, and shared ownership within SFA, ensuring all initiatives are executed in partnership with EO&T and Single Family Data.
Data Product Development: Support the creation and adoption of standardized, high-quality Data Products for SFA, aligned with enterprise data standards and evolving SFA business needs.
Metrics & Transparency: Establish and track metrics/KPIs to monitor progress, quality, and adoption of SFA data modernization initiatives, providing clear updates to SFA stakeholders.
Risk Reduction & Efficiency: Guide SFA teams in retiring legacy platforms, reducing operational risk, and streamlining data controls through improved governance and modern architecture.
Stakeholder Engagement: Build strong relationships across SFA business and technology teams, empowering partners to actively participate in SFA data modernization efforts.
Communication & Change Management: Develop compelling written materials and presentations to communicate the vision, progress, and benefits of SFA data modernization—including how SFA data enables innovation and transformation—to diverse audiences.