Job Title: Backend Developer for API Integration: PartnerBoost (Datafeed) to Google Ads Automation

Project Overview We are looking for an experienced backend developer to build an automated campaign deployment pipeline from scratch. The system will sit between PartnerBoost (an affiliate platform) and Google Ads, pulling product links in real-time, injecting unique dynamic attribution tracking tokens, and deploying structured search campaigns directly via the Google Ads API. The Core Problem to Solve Currently, our automated setup applies a single, hardcoded Amazon Attribution Campaign ID (aa_campaignid) across all products, or strips out the tracking parameters entirely. In Amazon Attribution, each brand/provider has its own unique Campaign ID. Hardcoding one ID across different brands or stripping the parameters breaks tracking and results in zero commissions. We need a system that fetches and maps these unique links via API in real-time and pushes them directly to Google Ads hierarchically, avoiding flat CSV files completely. System Architecture & API Integration Flow Trigger / Product Input: The system receives a list of products (ASINs/SKUs). Real-Time Mapping (PartnerBoost API): The system queries the PartnerBoost API, extracts the unique tracking string for that specific product, and builds the valid URL. Direct Deployment (Google Ads API): The system programmatically generates and launches the campaign structure directly into our Google Ads account. [Product Input] --► [PartnerBoost Datafeed API] --► [Dynamic URL Compiler] --► [Google Ads API Push] Detailed Developer Requirements & Tasks Task 1: Real-Time PartnerBoost API Integration Endpoint: Connect to the Publisher Datafeed API: https://app.partnerboost.com/api.php?mod=datafeed&op=list Logic: For every requested product, parse the payload response and look at the tracking_url field provided by PartnerBoost. Dynamic Extraction: Programmatically extract the unique, product-specific parameters: aa_campaignid and maas. Do not hardcode or globalize these IDs. They must be mapped dynamically per product/brand. Task 2: Dynamic URL Compilation Assemble the Final URL for the Google Ads system by merging the unique PartnerBoost parameters with Google Ads dynamic value-track macros. The mandatory format must look like this: https://www.amazon.com/dp/ASIN?maas=PRODUCT_SPECIFIC_MAAS&ref_=aa_maas&tag=maas&aa_campaignid=PRODUCT_SPECIFIC_PB_ID&aa_adgroupid=adgroupid&aa_creativeid=creative Constraint: If a product doesn't return a valid attribution string from the API, the system must log an error and skip it, rather than falling back to a global fallback ID. Task 3: Google Ads API Integration (Direct Hierarchical Push) Instead of generating flat CSV spreadsheets (which fail in Google Ads Editor due to row ambiguity), you must use the native Google Ads API to construct and push the campaign following its structural hierarchy: Campaign Level: Create the campaign object, set the daily budget, target country, and bidding strategy. Ad Group Level: Create Ad Groups under the campaign. Keyword Level: Inject Ad Group Keywords with specified Match Types (BROAD, PHRASE, etc.). Ad Level: Inject responsive_search_ad (RSA) objects containing Headlines, Descriptions, and the dynamically compiled Final URL. Deliverables Fully functional, modular code (Python or Node.js preferred) ready to be deployed. Clean configuration file (.env) for storing API Keys, Developer Tokens, and OAuth credentials for both Google Ads and PartnerBoost. Basic error logs to track skipped products or API rate limit issues. Skills Required Strong experience with Google Ads API (REST or Client Libraries). Deep understanding of API integration, JSON parsing, and URL parameter handling. Experience with Affiliate tracking platforms or Amazon Attribution is a huge plus.