Data Engineer

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.

About You

You are intellectually curious, possess good problem-solving skills, and always strive to deliver high-quality work. You are an effective communicator and break down technical challenges for non-technical audiences. You have a strong sense of ownership and like to solve technical puzzles. In the face of ambiguity, you keep a cool head and consider the trade-offs of the choices in front of you. When data outages occur, you switch your course of action and prioritize tasks effectively. You embrace feedback as a chance to grow. You generously share your learnings with others.



What You’ll Do


Work together with a highly talented and motivated team of engineers to ensure that our customers can count on Alloy’s data platform providing them data promptly and reliably every day.

Build, maintain, and improve data integrations that extract, transform, and load data from various, disparate retailer data sources into a standardized schema for our data platform.

Collaborate closely with other engineers, Product, and Client Solutions in cross-functional project teams to develop and build new features that enhance the capabilities of our data platform and product as we continue to scale our business.

Become intimately familiar with data pipelines, cloud infrastructure, supply chain and logistics fundamentals, and a whole host of other technologies and concepts.

Get to know the data back office of many retailers you know from your daily shopping and learn more about some of your favorite brands’ businesses.

Contribute to Alloy.ai’s engineering roadmap by bringing your ideas into our product development cycle.



What We Are Looking For

A Bachelor’s degree in a quantitative discipline (e.g., computer science, statistics, mathematics), a related field, or equivalent work experience.

1+ years of full-time work experience - including internships - in a similar position working with data pipelines and Extract, Transform, Load (ETL).

A good understanding of core Data Engineering concepts such as ETL, batch processing, data modeling, and schema normalization across inconsistent data sources.

Fluent in at least one programming language; preferably work experience of 1-2 years in Python, functional programming experience in Python is a plus. Nice to have: work experience in Java. 

Experience working with relational databases, such as PostgreSQL.

Interest in learning how the global supply chain works, from retail sales and inventory data to tracking of orders and shipments.

Nice to have: Experience working with browser automation, web scraping, APIs (REST, GraphQL), and EDI.

Nice to have: Experience working with one or more of the major cloud infrastructure providers (AWS, Google Cloud, Microsoft Azure) and their solutions for storage, orchestration, and telemetry.