What are the responsibilities and job description for the Data Engineer position at Underdog.io -Apply to top tech jobs in 60 seconds. A place where companies apply to you?
Location: New York City (in-office 4 days per week)
Employment Type: Full-time
About the Company
The company has built an agentic AI platform designed specifically to drive success for multi-unit franchise owners—covering everything from initial brand discovery to ongoing portfolio management.
- For prospective franchisees: The platform’s AI agents identify the most relevant franchise opportunities and guide users through the process of building a profitable multi-unit portfolio.
- For current operators: The AI agents automate routine workflows, surface actionable insights, and uncover new growth opportunities.
- For brands: The platform connects brands with a well-qualified pipeline of ambitious franchisees while streamlining time‑intensive franchise development processes.
Franchising represents a massive market with over 800,000 locations in the United States, nearly one trillion dollars in annual consumer spending, and a rapidly expanding international footprint. Multi‑unit operators now account for more than half of all franchise locations, yet the tools and infrastructure available to build and scale these portfolios remain fragmented and outdated. The company is solving this problem with support from leading venture investors, angel investors, and franchise industry veterans.
About the Role
The team is looking for a Data Engineer to build and own the data foundation that powers the platform and its AI agents. The business relies on a deep, continuously evolving dataset of public and proprietary information, and the company needs someone who can transform that raw complexity into clean, reliable, AI‑ready data.
This person will have end‑to‑end ownership of the data stack—from ingestion and transformation through modeling and downstream consumption. Their work will directly shape what the platform’s AI agents can do for operators and brands. Beyond the data layer, the role also offers opportunities to build entire products end‑to‑end, including owning the user experience.
What the Data Engineer Will Do
- Design and build scalable data pipelines that ingest, normalize, and enrich industry data from a wide range of structured and unstructured sources
- Own the data model and warehouse architecture that powers the product, AI agents, and internal analytics
- Build the infrastructure that makes industry data AI‑ready—including relational databases, vector stores, embeddings pipelines, feature stores, and retrieval layers
- Own 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 business intelligence and reporting: build the infrastructure and analyses that turn business data into clear, actionable insights; turn questions like “I wonder if…” into trusted answers, and shape what the team builds next based on the insights surfaced
- Explore new data sources and partnerships that expand the company’s industry knowledge graph across the franchise ecosystem
- Define data quality, observability, and lineage standards to increase data trust and reliability
- Shape how the company thinks about data as a long‑term competitive moat
Who the Company Is Looking For
- 6 years of data engineering experience, ideally in a product‑focused or AI‑driven environment
- Strong experience designing and operating production data pipelines—batch and streaming, structured and unstructured
- Comfortable with modern data warehouse / lakehouse technologies, orchestration tools, and transformation tooling
- Comfortable working with unstructured data and supporting AI/ML workloads
- Strong data modeling instincts and high standards for data quality, observability, and reliability
- High ownership mindset: treats the data stack as a core product pillar and holds themselves accountable to a high standard
- Curious and ambitious: enjoys going deep on messy real‑world data and turning it into genuine customer impact
- Bias for action: ships and iterates quickly without waiting for perfect conditions or complete information
- AI‑native: already uses AI coding tools to amplify personal impact and velocity; even if their current company does not lean heavily on AI, they regularly use AI tools on their own and are eager to work in an environment that makes AI a core pillar
- Startup or early‑stage experience is a plus
- Interest in franchising and local businesses is a plus
Why Join the Company
- Meaningful impact: Help support local communities by empowering local operators and elevating great franchise brands
- Ownership and responsibility: Own significant pieces of the business and have direct influence on company direction
- AI‑native culture: Join a team that is pushing the boundaries of what AI can do, both for the product and for how the team operates internally
- Strong benefits: Fully covered healthcare options and unlimited PTO
- In‑person team: Work alongside the founding team in New York City