Data Engineer

About the Company

Our hiring partner is building the first agentic AI platform designed to power multi‑unit franchise success, covering the entire journey from brand discovery to portfolio management. They serve three core customer groups: prospective franchisees seeking the right opportunities, current operators automating workflows and uncovering critical insights, and established brands connecting with a qualified pipeline of ambitious partners.

Franchising is a massive, trillion‑dollar industry with over 800,000 locations across the U.S. and a rapidly expanding international footprint. Multi‑unit operators now control more than half of all franchise locations, yet the infrastructure required to build and scale these portfolios remains fragmented and outdated. Backed by leading investors and industry experts, this team is modernizing the ecosystem and unlocking its full potential.

This company is seeking a Data Engineer to build and own the foundational data layer that powers their platform and AI agents. The business is built upon a deep, continuously evolving dataset of public and proprietary information, and this role is critical to transforming that raw complexity into clean, reliable, AI‑ready data.

This position offers end‑to‑end ownership of the data stack—from ingestion and transformation through modeling and downstream consumption. The work will directly shape what the AI agents can deliver for operators and brands. Beyond the data layer, this role also provides the opportunity to build entire products end‑to‑end, including owning aspects of the user experience.

• Design and build scalable data pipelines that ingest, normalize, and enrich industry data from a wide array of structured and unstructured sources.
• Own the data model and warehouse architecture that powers the core product, AI agents, and internal analytics functions.
• Build the infrastructure required to make industry data AI‑ready, including relational databases, vector stores, embeddings pipelines, feature stores, and retrieval layers.
• Take ownership of data‑centric features end‑to‑end: manage the underlying data, build AI‑powered matching engines, configure user‑facing agents, and ship the frontend experiences that surface data‑driven insights and opportunities to users.
• Own the business intelligence and reporting function, building the infrastructure and analyses that turn business data into clear, actionable insights. Transform raw questions into trusted answers and use the insights surfaced to help shape the product roadmap.
• Explore new data sources and partnerships to expand the company's industry knowledge graph across the franchise ecosystem.
• Define and implement standards for data quality, observability, and lineage to increase trust and reliability in the data.
• Play a key role in shaping the long‑term data strategy as a competitive moat.

• Possesses 6+ years of data engineering experience, ideally within a product‑focused or AI‑driven environment.
• Has strong, proven experience designing and operating production data pipelines, including both batch and streaming, and handling structured and unstructured data.
• Is comfortable and experienced with modern data warehouse and lakehouse technologies, orchestration tools, and transformation tooling.
• Has experience working with unstructured data and supporting AI and machine learning workloads.
• Demonstrates strong data modeling instincts and maintains high standards for data quality, observability, and reliability.
• Embraces a high‑ownership mindset, treating the data stack as a core product pillar and holding oneself accountable to a high standard.
• Is naturally curious and ambitious, with a passion for digging deep into messy, real‑world data and turning it into tangible customer impact.
• Has a strong bias for action, iterating and shipping features quickly without waiting for perfect conditions or complete information.
• Is fully "AI‑native," leveraging AI coding tools to amplify personal velocity and impact. This individual is eager to work in an environment where AI is a core pillar of both the product and internal operations, even if their current…