# Amazon Jobs Scraper - Low-costπŸ’²πŸ”₯πŸš€πŸ’Ό (`delectable_incubator/amazon-jobs-scraper---low-cost`) Actor Scrape Amazon jobs data πŸ’ΌπŸŒ with a powerful job scraper. Extract job titles, job IDs, locations, posting dates, descriptions, and URLs. Ideal for job market analysis, recruitment intelligence, hiring trend tracking, and talent sourcing with structured datasets at scale πŸ“ŠπŸš€ - **URL**: https://apify.com/delectable\_incubator/amazon-jobs-scraper---low-cost.md - **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community) - **Categories:** Jobs, Developer tools, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.00005 / actor start This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README

Amazon Jobs Scraper - PrimeScrape

--- ### Amazon Jobs Scraper πŸ’ΌπŸ“ŠπŸš€ The Amazon Jobs Scraper is a fast, reliable, and scalable automation tool designed to extract structured job listings directly from Amazon Jobs. It transforms raw job postings into clean, structured datasets ready for recruitment intelligence, hiring trend analysis, talent sourcing, and data-driven applications. --- ### Amazon Jobs Scraper πŸ§ πŸ’ΌπŸ“ˆ This scraper automatically extracts structured job listings from Amazon Jobs based on search result URLs. Ideal for recruiters, analysts, HR tech platforms, developers, and job market researchers. --- ### 🎯 What This Scraper Does Simply provide one or multiple Amazon Jobs search URLs and the number of items to extract, and the scraper will automatically collect structured job data. βœ… Extracts job listings from Amazon Jobs βœ… Supports search result pages βœ… Handles pagination automatically βœ… Respects max items per URL limits βœ… Extracts job descriptions & qualifications βœ… Captures posting dates and metadata βœ… Structures data for analytics & integrations βœ… Ready for dashboards, ATS, and pipelines --- ### πŸ“Š Data Extracted πŸ’Ό Job Fields | Field | Description | | ------------------- | -------------------------------------- | | πŸ†” `jobId` | Unique Amazon job ID | | πŸ’Ό `jobTitle` | Job position title | | πŸ“ `location` | Job location (city / country / remote) | | πŸ“… `postedDate` | Job posting date | | πŸ“ `description` | Full job description | | 🎯 `qualifications` | Required / preferred qualifications | | ⏱ `scrapedAt` | Date & time the job was scraped | | πŸ”— `jobUrl` | Direct job application URL | --- ### πŸ›  How to Use 1️⃣ Configure Input Provide one or multiple Amazon Jobs URLs: ```` { "target\_url": \[ "https://amazon.jobs/en/search?base\_query=ai\&job\_type%5B%5D=Full-Time" ], "max\_items": 40 } ``` 2️⃣ Run the Actor The scraper will: β€’ Open Amazon Jobs search pages β€’ Automatically paginate results β€’ Extract job listings β€’ Collect descriptions & qualifications β€’ Structure and clean the dataset β€’ Stop when max_items limit is reached 3️⃣ Export the Dataset Download your results in multiple formats: βœ… JSON βœ… CSV βœ… Excel βœ… XML βœ… HTML --- ### βš™οΈ Input Configuration #### πŸ“₯ Input Example ``` { "target\_url": \[ "https://amazon.jobs/en/search?base\_query=ai\&job\_type%5B%5D=Full-Time" ], "max\_items": 40 } ``` #### Input Fields | Field | Type | Description | | ------------ | ------- | -------------------------------------- | | `target_url` | array | List of Amazon Jobs search URLs | | `max_items` | integer | Maximum number of job listings per URL | --- ### πŸ“€ Output Example ``` { "jobId": "AMZN123456", "jobTitle": "Applied Scientist – AI", "location": "Berlin, Germany", "postedDate": "2026-01-28", "description": "We are looking for an Applied Scientist to join the AI team...", "qualifications": "PhD or MSc in Computer Science, ML experience...", "scrapedAt": "2026-02-09T12:30:00Z", "jobUrl": "https://amazon.jobs/en/jobs/AMZN123456" } ```` --- ### πŸ“Š Output explanation | Field | Description | | ---------------- | --------------------------- | | `jobId` | Unique job identifier | | `jobTitle` | Job title | | `location` | Job location | | `postedDate` | Publication date | | `description` | Full job description | | `qualifications` | Job requirements | | `scrapedAt` | Scraping timestamp | | `jobUrl` | Direct job application link | --- ### 🌍 Why Use This Scraper? πŸ’Ό Recruitment Intelligence β€” Analyze Amazon hiring patterns πŸ“Š Job Market Analysis β€” Track demand by role & location πŸ“ Location Insights β€” Identify hiring hotspots ⏰ Fresh Opportunities β€” Monitor newly posted jobs πŸ”„ Automation β€” Schedule recurring extractions πŸ€– Data Pipelines β€” Feed structured data into your systems ⚑ Scalable β€” Built for high-volume scraping --- ### ⚠️ Disclaimer This tool is an independent solution and is not affiliated with or endorsed by Amazon. --- ### πŸ’Έ Pricing This scraper runs on a **pay per events subscription model**. You only pay for **successful runs**. πŸ’³ **Price:** $4.79 / 1000 results --- ### Related Actors If you're interested in other Cooking scrapers, explore more scrapers (Coming soon) --- ### πŸ“¬ Support ⭐⭐⭐⭐⭐ Leave a 5-star rating if you like this tool --- ### 🌍 PrimeScrape Built for scalable web data extraction & automation Contact for custom scraping solutions or enterprise requests via Apify or by email. # Actor input Schema ## `target_url` (type: `array`): One or more Amazon jobs search URLs to scrape (e.g., 'https://amazon.jobs/en/search?base_query=ai&job_type%5B%5D=Full-Time') ## `max_items` (type: `integer`): Maximum number of job listings to scrape per URL ## Actor input object example ```json { "target_url": [ "https://amazon.jobs/en/search?offset=0&result_limit=10&sort=relevant&job_type%5B%5D=Full-Time&base_query=ai" ], "max_items": 50 } ```` # Actor output Schema ## `overview` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "target_url": [ "https://amazon.jobs/en/search?offset=0&result_limit=10&sort=relevant&job_type%5B%5D=Full-Time&base_query=ai" ], "max_items": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("delectable_incubator/amazon-jobs-scraper---low-cost").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "target_url": ["https://amazon.jobs/en/search?offset=0&result_limit=10&sort=relevant&job_type%5B%5D=Full-Time&base_query=ai"], "max_items": 50, } # Run the Actor and wait for it to finish run = client.actor("delectable_incubator/amazon-jobs-scraper---low-cost").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "target_url": [ "https://amazon.jobs/en/search?offset=0&result_limit=10&sort=relevant&job_type%5B%5D=Full-Time&base_query=ai" ], "max_items": 50 }' | apify call delectable_incubator/amazon-jobs-scraper---low-cost --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=delectable_incubator/amazon-jobs-scraper---low-cost", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Jobs Scraper - Low-costπŸ’²πŸ”₯πŸš€πŸ’Ό", "description": "Scrape Amazon jobs data πŸ’ΌπŸŒ with a powerful job scraper. \n\nExtract job titles, job IDs, locations, posting dates, descriptions, and URLs. \n\nIdeal for job market analysis, recruitment intelligence, hiring trend tracking, and talent sourcing with structured datasets at scale πŸ“ŠπŸš€", "version": "0.0", "x-build-id": "BrQ9VWCcaugccd0zM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/delectable_incubator~amazon-jobs-scraper---low-cost/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-delectable_incubator-amazon-jobs-scraper---low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/delectable_incubator~amazon-jobs-scraper---low-cost/runs": { "post": { "operationId": "runs-sync-delectable_incubator-amazon-jobs-scraper---low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/delectable_incubator~amazon-jobs-scraper---low-cost/run-sync": { "post": { "operationId": "run-sync-delectable_incubator-amazon-jobs-scraper---low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "target_url", "max_items" ], "properties": { "target_url": { "title": "Target URLs πŸ”—", "type": "array", "description": "One or more Amazon jobs search URLs to scrape (e.g., 'https://amazon.jobs/en/search?base_query=ai&job_type%5B%5D=Full-Time')", "default": [ "https://amazon.jobs/en/search?offset=0&result_limit=10&sort=relevant&job_type%5B%5D=Full-Time&base_query=ai" ], "items": { "type": "string" } }, "max_items": { "title": "Maximum Jobs to Scrape per URL πŸ”’", "type": "integer", "description": "Maximum number of job listings to scrape per URL", "default": 50 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```