Data Infrastructure & Self-Service Analytics for E-Commerce Brand

We're a mid-size UK beauty brand (DTC, ~16 people) sitting on a lot of data we're not using well enough. We already run BigQuery and Airbyte, but the setup has grown organically and nobody's fully mapped what we have, what's stale, and what's missing. What we want to get to: a setup where any team lead can pull their own reports and ask plain-language questions against our data — no tickets, no waiting on a data person. Scope: - Data audit — Review our current BigQuery warehouse and Airbyte connections. Tell us what's working, what's broken, and what gaps exist. - Source connectivity — Wire up all our sources into BigQuery via Airbyte. The list includes Shopify, Meta Ads, Google Ads, Klaviyo, GA4, Xentral, Zendesk, Amazon Seller Central, TikTok Ads, Taboola, and a few Google Sheets. - Transformation layer — Build dbt models that turn raw data into clean, documented, query-ready tables across Marketing, Sales, and Operations. - Dashboarding — Stand up Metabase (open to cloud or self-hosted), connect it to BigQuery, and build 5–8 dashboards covering our key KPIs. - AI/natural-language querying — Enable the team to ask ad-hoc questions in plain English against the warehouse (Metabase AI or similar). - Handover — Written docs + short Loom videos so team leads can onboard themselves. You should know: BigQuery, Airbyte, dbt, Metabase, and data modeling. Logistics: Fixed-price with milestones preferred — send a proposal with your breakdown Timeline: 4–10 weeks Fluent English