Full-Stack Engineer (Next.js + Supabase) with Strong Data-Cleaning Skills

We're building a data-driven platform in the beauty/cosmetics space. We've already collected a very large volume of scraped product and brand data, and it's messy - inconsistent formats, duplicates, missing fields, mixed languages, and unreliable values. Your job is to turn that raw data into something clean and reliable, and to build the web application on top of it. This is not a quick gig. We're looking for someone to stay with us for roughly a year and grow with the product. What you'll be doing Building and maintaining a Next.js (App Router) front end and back end Designing and managing our Supabase setup (Postgres schema, RLS policies, auth, storage, edge functions) Cleaning, normalizing, and deduplicating large beauty datasets (this is a major part of the role) Building data pipelines to process and validate incoming scraped data Writing transformation/normalization logic (units, brand names, categories, ingredients, pricing, etc.) Setting up data-quality checks and monitoring Iterating on features with us as the product evolves You should have Strong production experience with Next.js and Supabase (please point to specific projects) Solid SQL/Postgres skills - not just ORMs Real experience cleaning and normalizing large, messy datasets (Python/pandas or similar is a plus) Comfort working with scraped data and all the inconsistencies it brings Good written English and reliable communication Ability to work independently and own your part of the product Nice to have Experience in e-commerce, catalog, or product-data projects Familiarity with data pipelines / ETL tooling Some ML/NLP experience for entity matching or text cleanup Budget We expect this to run around $4,000–$5,000 USD per month depending on experience and hours. This is a long-term commitment, so stability and quality matter more to us than the lowest rate. To apply, please include: Similar past work - links or short descriptions of Next.js + Supabase projects, and at least one data-cleaning/normalization project you've done. Your time zone and your typical available hours - we need to know there's reasonable overlap. Your expected monthly budget within the range above (or your rate if hourly). Applications that don't address all three points will not be considered. A short note on how you'd approach cleaning messy beauty product data is a big plus. We read every proposal carefully and respond quickly to strong candidates. Looking forward to working with you.