$112.6K – $152.8K/yr
Pay vs market · Bottom quarter
This job's pay ($97,500 a year at the midpoint) is lower than over 90% of 57 salary-listed Data Engineer jobs in United States in the last 12 months; their median is $190,000.
Role overview
Job description
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.
About this listing
- Source: Alloy.ai's official careers site (via Lever) · last confirmed on the source 3 Nov 2026
- Posted 14 Sept 2026
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What they are looking for
Skills & requirements
Qualification
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
Department · Engineering
Hiring company
Alloy.ai
View the company profile, current openings and hiring details.
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