Lead Analytics/ Data Engineer

Title: Lead Analytics/ Data Engineer Location: Remote Non-Negotiables: • Must have retail/ecommerce recent background – this company is a online clothing brand – needs similar background industry experience • This role centers on owning and governing our Looker semantic layer specifically – deep looker and LookML expertise • Needs smaller / startup company recent experience. Someone who has only worked for huge companies will NOT work. • Ownership of a single retail/ecommerce company's Looker + Snowflake + Shopify/NetSuite/daasity/toolio/fivetran stack Job Description Establish and enforce naming, ownership, and documentation standards for Snowflake schemas and objects — including flagging tables with no downstream Looker reference or owned by generic/departed-employee service accounts Build and maintain reconciliation logic between systems (e.g., Shopify ↔ NetSuite ↔ Avalara tax reconciliation, order status/fulfillment lifecycle across Shopify → NetSuite → Twin Oaks) Design, build, and refactor LookML models, explores, views, and derived tables that map cleanly to underlying Snowflake objects — not 1:1 dashboard-driven sprawl Required Qualifications • 7+ years in BI/analytics engineering with production Looker/LookML experience (models, explores, derived tables, PDTs, access filters) — not just dashboard consumption • 4+ years of advanced SQL in Snowflake or a comparable cloud warehouse (window functions, incremental merge patterns, query performance tuning) • Direct experience with retail/ecommerce data models: order lifecycle, fulfillment, inventory, returns, customer/CDP data — ideally spanning a DTC platform (Shopify/BigCommerce/Salesforce Commerce) plus an ERP (NetSuite, Microsoft Dynamics, SAP) • Experience working within a vendor-managed or templated ELT/transformation framework (Daasity, Fivetran + dbt, Matillion, or similar) — comfortable extending vendor patterns without introducing untracked one-offs