Data Engineer

About Alloy.ai

At Alloy.ai, we work with consumer goods companies that make the products we eat, wear, and use every day, as well as the ones we occasionally splurge on. We’re tackling a real and complex problem for them—managing supply and demand in the face of constantly changing customer behavior, highly complex supply chain networks, 40-year-old data standards, and labor-intensive manual processes. 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, offering more than 400 active integrations to connect and harmonize our customers’ data from a variety of sources. Our customers rely on Alloy.ai to provide accurate and complete data in a timely manner to run their businesses. Data Engineers are responsible for building, maintaining, and expanding these integrations while utilizing monitoring tools to detect and address any data issues. We continuously improve our data pipeline as our business grows to ensure our customers receive the highest value from their data.

About You

To succeed in the role of a Data Engineer, you should possess curiosity, creativity, and effective problem-solving skills with strong communication capabilities. You can expect a blend of building data integrations, maintenance, and feature development, including:

• Writing production-grade Python code for our data pipeline that processes customer data.
• Connecting external systems using web scraping, APIs, ODBC, AS2, and more.

What You Will Do

• Collaborate with a motivated team of engineers to ensure our customers rely on Alloy's data platform for timely and reliable data.
• Build, maintain, and improve data integrations that extract, transform, and load data from various retailer sources into a standardized schema.
• Work closely with engineers, Product, and Client Solutions to enhance integrations and expand available data types and sources.
• Participate in cross-functional teams to develop new features that enhance our data platform's capabilities as we scale.
• Become familiar with data pipelines, cloud infrastructure, and supply chain fundamentals while contributing to Alloy.ai’s engineering culture.

What We Are Looking For

• Bachelor’s degree in a quantitative discipline (e.g., computer science, statistics, mathematics) or a related field.
• 1-2 years of full-time work experience in a similar position, particularly with data pipelines and Extract, Transform, Load (ETL).
• Good understanding of core Data Engineering concepts such as ETL, batch vs. stream processing, data modeling, and data warehousing.
• Fluency in at least one object-oriented programming language, preferably 1-2 years of work experience in Python; bonus points for experience in Java.
• Familiarity with relational databases (e.g., Postgres) and ability to write database queries; working knowledge of cloud service suites (AWS, Google Cloud, Microsoft Azure) is a plus.
• Interest in understanding the global supply chain, from retail sales data to order tracking.
• Genuine desire to support fellow engineers through mentorship, pairing, and code reviews.
• Ability to effectively prioritize tasks during data outages.
• Strong verbal and written communication skills, with the ability to translate technical details for non-technical audiences.

Role is a hybrid position based in Washington, DC, defined as 3+ days per week in the office when not on vacation. Remote employees will not be considered for this role.