Alloy

Data Engineer

Washington, DC

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hirly's read of this role

Role family: Data & ML
Seniority: Mid level
Stated salary: $85,000 – $110,000 per year
Country: US
Work mode: On-site / unstated
First seen by hirly: 18 Sept 2026

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the posting

About Alloy.ai

Alloy.ai is the Commerce Intelligence System for consumer brands. We unify data from 500+ sources — ERPs, retailers, ecommerce platforms, and distributors — into a single source of truth your team can bet their P&L on. Our proprietary commerce logic and AI Agents translate fragmented data into clear demand signals and prepare execution-ready actions — automatically. Sales and Supply Chain teams at brands like Liquid I.V., Crayola, and Valvoline use Alloy.ai to capture every revenue window, protect margins, and keep products on the shelf. From signal to action. Instantly.

Alloy.ai is a fast-growing, well-funded startup with an expanding presence across the world. Our team hails from successful startups, leading tech companies and Fortune 100 enterprises. We believe deeply in fostering individual ownership, iterating to excellence, focusing on what matters, communicating openly & respectfully, and supporting one another.

We encourage people of all backgrounds to apply. Alloy.ai is committed to creating an inclusive culture, and we celebrate diversity of all kinds.

About The Role

Our data platform is an integral part of Alloy.ai’s value proposition. We offer 450+ active integrations to connect and harmonize our customers’ data from a variety of data sources (retailers, e-commerce, distributors, ERP). Our customers rely on Alloy.ai to provide accurate and complete data in a timely manner to make data-driven business decisions.

Our small but growing team of Data Engineers is responsible for building, maintaining, and expanding these integrations, monitoring for data outages, and improving our ingestion tooling. The team works across the full range of integration technology: web scraping and browser automation, APIs, and domain-specific standards like EDI. We build many of the tools we work with, from our in-house data transformation DSL to the agentic development tools we use to build and debug integrations.

We own data tooling that other internal teams and our customers alike use to set up and manage data integrations. Our goal is to grow the data platform into a central data repository for our customers that scales with the complexity of their businesses and tech stack.

You can learn more about our technology stack and engineering values at https://alloy.ai/engineering .

Original posting on Alloy's site ↗

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