Data and Analytics Engineer

About Us

Resonance is transforming the fashion industry by building a more sustainable and valuable ecosystem for designers, brands, manufacturers, consumers, and the planet. Our AI-powered operating system, ONE, empowers brands to design, sell, and make products efficiently and sustainably. Resonance ONE drives end-to-end garment creation with minimal environmental impact, eliminating overproduction and unnecessary inventory.

With headquarters in New York City and Santiago, Dominican Republic, Resonance partners with leading brands—including THE KIT and Rebecca Minkoff—to significantly reduce resource use: 97% less dye, 70% less water, and 50% less material compared to traditional fashion brands.

About the Role

We’re seeking a talented Data and Analytics Engineer to build, maintain, and scale our data infrastructure. You’ll play a crucial role in shaping our analytical capabilities, enabling Resonance to leverage data-driven insights effectively across our complex, integrated technology stack.

In this role, you’ll develop and maintain robust ELT pipelines, transforming data from diverse sources—including telemetry data, Shopify, SendGrid, CreateOne, and other internal platforms—into structured, accessible datasets within Snowflake. Additionally, you’ll craft sophisticated LookML models to power interactive analytics, dashboards, and explorers used daily by our business teams.

Responsibilities

• Design, build, and maintain scalable ELT pipelines that reliably transform raw data from sources such as Shopify, SendGrid, telemetry services, and proprietary applications (CreateOne) into our Snowflake data lake and data warehouses.
• Create efficient, maintainable data models within Snowflake that serve as the foundation for analytics, reporting, and data-driven decision-making.
• Develop and refine LookML models, enabling intuitive exploration, dashboards, and actionable analytics for non-technical business users.
• Collaborate closely with product teams, engineers, and business stakeholders to identify data needs, gather requirements, and deliver high-impactdata solutions.
• Continuously improve data quality, governance, and accessibility, implementing best practices for data management and compliance.
• Proactively monitor and optimize ELT performance, reliability, and cost-effectiveness.
• Stay updated on the latest data engineering technologies, approaches, and analytics tools to ensure Resonance maintains industry-leading capabilities.