Data Engineer: build our BigQuery warehouse from e-commerce, marketplace, ad and ERP data

We run a small family of body-care brands, sold on Shopify, Amazon, Walmart and TikTok Shop and in retail stores, and advertised on Meta, TikTok, Snapchat and Google. Our books run in NetSuite. Today our data lives in each platform’s own dashboards, a few third-party tools, and an internal app that pulls some of it into Postgres. We want all of it in one BigQuery warehouse that we own: every source ingested reliably, cleaned, and modeled relationally, so orders, products, fees, payouts, inventory and ad spend connect to each other and to the transactions in our ledger. You’d be our first dedicated data person, designing and building that warehouse. You’d work day to day with our operations lead, who builds the reporting on top of it. You’d also work with our accounting team wherever the data touches the books, so that sales, fees, refunds and payouts map to how they’re recorded in NetSuite. What you’ll do: - Get to know our sources and how we use the data, then decide what to build first - Build reliable ingestion into BigQuery from: Sales channels: Shopify, Amazon (SP-API and Ads), Walmart, TikTok Shop - Ad platforms: Meta, TikTok, Snapchat and Google Ads NetSuite and retail sales files - Design a relational model where one product connects across every channel’s SKUs and bundles, and revenue, fees and ad spend roll up correctly - Connect operational data to accounting, with the accounting team: marketplace settlements and payouts, fees, refunds and returns, and how each maps to our chart of accounts - Reconcile the warehouse against each platform and the ledger, and fix what doesn’t match Keep it simple enough that a small team can run and extend it What we’re looking for: - Strong BigQuery and SQL, plus Python for pipelines Experience designing relational data models, not just loading raw tables - Hands-on work with e-commerce, marketplace or ad platform APIs. Shopify, Amazon SP-API, Walmart and TikTok Shop are a big plus. - A working grasp of accounting, ideally US GAAP: general ledger and chart of accounts, revenue versus payouts, fees, refunds, and why a channel’s sales figure rarely matches what hits the bank - Experience with an ERP, ideally NetSuite, or close work with an accounting or finance team - You’ve built a warehouse or pipelines mostly on your own, not just maintained a piece of a large one - Clear written communication. You’ll explain what you found and why the numbers moved, to operators and accountants alike. Nice to have: -dbt or Dataform -Google Cloud scheduling and deployment (Cloud Run, Cloud Functions, Scheduler) -Contribution margin, attribution or retail sales data 3PL or inventory data How we hire: after reviewing proposals, we send shortlisted candidates a short written exercise (about 15-30 minutes) and then talk with those whose answers stand out. To apply, answer briefly in your proposal: - Tell us about a data warehouse or pipeline you built mostly on your own. What went into it? - Which of our sources have you worked with directly, and have you worked with an ERP or an accounting team? If so, how did ledger data fit into what you built? - Start your proposal with the word “Ledger” so we know you read this far. In addition at the very end of your proposal write simply Yes or No with no explanation to answer the following question: Did you use AI to help you write your proposal? We dont care either way just curious.