Direct-to-consumer wine marketplace with regional fulfillment and analytics transformation
Naked Wines operates a D2C wine platform connecting independent winemakers directly to consumers across UK and US markets. The company is mid-stage in a major data and logistics overhaul: active projects span multi-region fulfillment, ERP migration, and a wholesale rebuild of analytics infrastructure (end-to-end tracking, server-side conversion APIs, unified data layer via dbt). The hiring mix—7 data roles out of 16 open posts, predominantly senior and lead levels—signals this is not incremental optimization but structural modernization of the tech foundation.
Naked Wines is a publicly listed wine retailer operating a membership model where customers purchase directly from independent winemakers. The company operates in both the UK (headquarters in Norwich) and the United States. The platform uses Shopify and Salesforce Commerce Cloud as commerce engines, with BigQuery, dbt, and Looker forming the analytics layer. Current operational priorities include stabilizing a three-party logistics network across regions, completing an ERP transformation, and closing gaps in analytics adoption and data governance. The company manages customer acquisition and media spend through Meta, Google, and programmatic testing (Optimizely, VWO).
Primary platforms are Shopify and Salesforce Commerce Cloud. Analytics runs on BigQuery and Looker, with data modeling in dbt. Customer data and conversion tracking uses Meta Conversions API and Google Analytics 4.
Yes. Data comprises 7 of 16 active roles (44% of hiring), mostly at senior and lead levels, reflecting investments in analytics infrastructure and ERP migration.
Headquartered in Norwich, England. Active operations and hiring span the UK and United States, with multi-region fulfillment and compliance requirements in both markets.
Naked Wines's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.