About the job
About Saaf AI
At Saaf AI, we are revolutionizing the mortgage lending landscape by harnessing the power of advanced artificial intelligence coupled with established lending practices. As a fintech startup integrated into American Heritage Lending—one of the nation's top ten private lenders, managing billions in loan volume across various programs—we are supported by some of the largest asset management firms and investment funds.
Our team is fundamentally AI-driven. Every engineer, product decision, and operational workflow is meticulously crafted to answer the question: “How can AI enhance efficiency, intelligence, and reliability?” If you are eager to expand the horizons of your expertise by utilizing the most advanced AI tools and methodologies daily, this role places you at the forefront of data architecture and analytics engineering as we move into 2026 and beyond.
The Role
We are seeking a Senior Data Architect & Analytics Engineer to lead the development and enhancement of our analytics data platform. As our first dedicated data hire, you will be a hands-on architect responsible for shaping how data drives decisions across underwriting, sales, and operations.
While the foundational work has been laid, the most thrilling and impactful challenges are still ahead. You will take charge of a platform ripe for growth: developing entity resolution across disparate real estate data, designing enrichment pipelines that convert raw data into actionable insights, constructing the semantic layer essential for AI-driven analytics, and refining the architecture as we expand into new loan programs and data sources.
This role is ideal for you if:
You have built and managed a comprehensive modern analytics stack from start to finish, rather than simply contributing to one.
Data integrity is your top priority from the outset—not an afterthought.
You thrive on enhancing a robust foundation and are driven to achieve ambitious goals.
You aspire to be the key data figure in a rapidly growing company—enjoying high ownership, significant impact, and a clear trajectory to team leadership.
What You’ll Own
Analytics Platform — Build It, Run It, Evolve It
Take complete ownership of the production data pipeline—from ingesting external real estate and borrower data to transforming it through a multi-layered model (staging → enrichment → business-ready marts) while ensuring its reliability.
Create and maintain the semantic layer—comprising model descriptions, metric definitions, and metadata that fuel BI dashboards, AI assistants, and self-service analytics.

