We are Tailor Brands. We built a platform that builds businesses. From launching and managing to growing a business, Tailor Brands is the all-in-one solution that empowers any business owner. Our platform services over 40 million small businesses.
Our "Guidance Engine" assesses each new business introduced to our platform and devises a tailored plan that allows you to manage all your business needs from a single dashboard. Through our business-building platform, we’re turning the process of starting, managing, and growing a business into a better experience; we’re simplifying the business journey. At Tailor Brands, we believe in more than just handing you another tool; we are dedicated to teaching you the art of building a business.
As a Data Engineer at Tailor Brands, you'll design and maintain the data pipelines that power decision-making across product, marketing, and finance. Working with Apache Airflow, Python, and SQL, you'll build trusted, well-documented datasets that enable self-service analytics for the entire organization.
You'll champion data quality through validation and monitoring, optimize infrastructure for scale, and be part of a forward-thinking team that actively leverages AI tools like Claude to push the boundaries of modern data engineering. If you thrive on turning messy data into reliable, actionable foundations — and want to do it for a platform serving over 40 million small businesses — this role is for you.
What we’re looking for
Design, implement and maintain pipelines that deliver data with measurable quality and SLAs for our product, marketing, finance, and other departments
Partner with business domain experts, data analysts, and engineering teams to build foundational datasets that are trusted, well-understood, aligned with business strategy and enable a self-service analysis
Focus on data quality, detect data/analytics quality issues, implement bug fixes and data validations for prevention
Identify, design, and implement internal process improvements such as automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc
Be part of a team that actively integrates AI tools like Claude into day-to-day workflows, pushing the boundaries of how data engineering gets done