Wallex Wallpapers: Smart Ranking and Grouped Variant Cards on Category Pages

We're looking for a developer to upgrade the category and collection pages on our wallpapers e-commerce website. Fixed price of $200 USD, paid as one milestone on completion. Goal: make the listing pages smarter and cleaner in two ways. First, rank products by real performance instead of a manual order. Second, group color variants of the same design under one card instead of showing each variant as its own tile. Background: the category pages currently show thousands of tiles, but many are just color variants of the same wallpaper, so the pages feel repetitive and real variety gets buried. Sorting today is driven only by a manual featured tag rather than actual sales or shopper behavior. We have around 10,000 SKUs, variants already share a group_id in the database, and Google Analytics 4 is already tracking product impressions, clicks, conversions, and purchases. Scope (4 subtasks, at a high level): 1) Backend, smart ranking: a daily job that blends sales data from our database with GA4 signals into a ranking score per product group. 2) Backend, listing query and grouping: return one row per group, sorted by the score, with the manual featured tag kept as a top-pin override. 3) Frontend, card redesign: a single group card with color swatches (with specific desktop and mobile behavior to be detailed). 4) Frontend, sort dropdown: popularity, newest, price low to high, price high to low. Recommended shipping order: subtask 1, then 2 (backend foundation), then 3 and 4 (frontend on top). Please review the scope, estimate each subtask, and propose a shipping order. Out of scope: individual product pages (PDPs), checkout, homepage layout, and per-user personalization. A short call will be held before starting to walk through the full spec and the details for each subtask. Deliverables: - All four subtasks implemented and tested on our category and collection pages. - Light testing on desktop and mobile. Timeline: to be agreed based on your estimate. Revisions: up to 2 rounds per subtask within scope. Ideal candidate: a full-stack developer comfortable with backend data work, GA4 data, and frontend UI. When applying, please briefly mention similar e-commerce listing or ranking work you've done.