Head of Data Product Engineering

## Exceed the expectations of our residential mortgage borrowers & business partners through superior service, simple processes, and effective communications.## We deliver on this mission by empowering our employees by encouraging and recognizing superior performance and innovative solutions, by promoting teamwork and divisional cooperation.
** POSITION SUMMARY
** The SVP Data Product Engineering will lead the transformation of Newrez’s data ecosystem into a modern, scalable, and AI-powered platform that enables faster, smarter lending decisions and operational excellence across origination, servicing, secondary marketing, and risk functions. This executive will architect and execute a data-as-a-product strategy that unifies fragmented systems, delivers trusted analytics at scale, and powers next-generation customer and portfolio insights.

The ideal candidate combines deep technical expertise in enterprise data engineering with product-centric leadership and a track record of driving measurable value in regulated financial environments.

You’ll lead global teams of engineers, product managers, and data scientists to design next-generation data products that strengthen origination, servicing, secondary marketing, and risk analytics. This role is ideal for a strategic builder who thrives at the intersection of architecture, innovation, and business transformation.
** DESCRIPTION
* *** Essential Functions, Duties, and Responsibilities
*** Develop and operationalize a data-as-a-product portfolio strategy that underpins core mortgage operations—from loan origination through servicing—and enables real-time, AI-driven analytics.
* Architect a modern data platform ecosystem that integrates structured, unstructured, and streaming data across internal systems and third-party partners.
* Lead the design, build, and scaling of AI-infused data products supporting pricing optimization, borrower intelligence, fraud detection, and servicing efficiency.
* Direct cross-functional global teams of data engineers, product managers, and data scientists to deliver enterprise-grade data solutions on time and within budget.
* Partner with technology, risk, finance, and business line leaders to translate business imperatives into scalable data products that drive growth, compliance, and customer retention.
* Define and monitor key product performance indicators—data quality, latency, adoption, and ROI—and drive continuous improvement.
* Championing a culture of experimentation, agility, and accountability, fostering rapid prototyping and iterative innovation.
* Ensure full adherence to mortgage data privacy, model governance, and regulatory requirements, including HMDA, FCRA, and CFPB standards.
* Collaborate with enterprise security, architecture, and compliance teams to embed data governance and lineage across the entire ecosystem.
* Ability to effectively and accurately convey information to others.
* Performs related duties as assigned by management.
** Qualifications and Education Requirements
*** Advanced degree in Computer Science, Engineering, Data Science, or related discipline.
* 15+ years of experience leading enterprise data, analytics, or platform modernization initiatives in large enterprises
* Proven success launching GenAI-enabled data products in hyperscaler marketplaces or enterprise production environments.
* Expertise integrating emerging technologies—generative AI, knowledge graphs, vector search—into traditional data ecosystems.
* Experience partnering with regulatory and risk teams to operationalize AI governance and ethical model frameworks.
* Proven ability to lead and scale distributed technical and product teams, balancing innovation with risk and compliance controls.
** Skills, Abilities, and Knowledge
*** Recognized leader with the ability to bridge business and technology, shaping strategic data roadmaps that accelerate growth and digital transformation
* Deep expertise in data engineering frameworks, ML/AI platforms, and enterprise SaaS architectures.
* Demonstrated success in designing and deploying data-driven platform architectures and AI-enabled analytics within large, regulated enterprises—preferably in…