{firstName},Does this align w/your potential interest – a Direct Hire/FT opportunity – Data Quality Engineer (Ecomm Analytics) for a fast-growing retail beauty company. You’d be joining an org with 20–30% YoY revenue growth, a founder-led team that values innovation, curiosity, and precision. They’re scaling a world-class data ecosystem to power marketing performance dashboards, LTV cohort models, and experimentation across every digital channel—and this role is central to making that happen.The Sr. Director (a thoughtful, empowering leader) is looking for someone who brings both deep technical skill and business context—you’ll understand why ecommerce metrics move, and make sure the org can trust that insight. From rebuy rate drops to LTV shifts or order volume spikes, your work will ensure the right people see the right signals at the right time.This is a hands-on engineering role. {firstName}, you’ll: Build & maintain scalable pipelines in Google Cloud / BigQuery Model data in dbt (with GitHub version control) Connect and integrate ecommerce, marketing, and analytics data sources (SQL + Python) Implement automated data quality checks, anomaly detection, and KPI alerts for DTC metrics Own documentation, enforce governance standards, and enable self-service analytics across the org Partner with engineering, marketing, and analytics teams to solve complex data challenges Looking for someone with 5+ years in data engineering/analytics engineering , strong SQL + Python , dbt , and cloud warehouse expertise ( BigQuery, Snowflake, or AWS ). A big bonus if you have direct DTC/Ecommerce analytics experience at the session/order level. Must love optimizing data systems, spotting anomalies, and enabling better decisions.Hybrid (NYC) role. Unfortunately, we are not able to provide sponsorship or transfer.