# Lever Jobs Scraper for Hiring Signal Data (`fetch_cat/lever-jobs-scraper`) Actor Export public Lever jobs with titles, teams, locations, URLs, descriptions, and timestamps for recruiting, sales signals, job boards, and hiring alerts. - **URL**: https://apify.com/fetch\_cat/lever-jobs-scraper.md - **Developed by:** [Hanna Nosova](https://apify.com/fetch_cat) (community) - **Categories:** Jobs - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.30 / 1,000 job postings This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## Lever Jobs Scraper Scrape public job postings from Lever-hosted company career pages and export clean hiring data for recruiting, lead generation, job-board ingestion, labor-market research, and workflow automation. ### What does Lever Jobs Scraper do? Lever Jobs Scraper collects public roles from companies that publish openings on Lever. It accepts one or more Lever company slugs, such as `spotify`, and returns structured job records. You can also paste full Lever board URLs such as `https://jobs.lever.co/spotify`. The actor returns job titles, job IDs, application URLs, hosted URLs, locations, departments, teams, work type, descriptions, and timestamps. ### Who is it for? Lever Jobs Scraper is for teams that need current hiring data from public company career pages. 👔 Recruiters use it to monitor which companies are hiring and where headcount is growing. 📈 Sales teams use it to find companies expanding specific departments. 🧑‍💻 Job-board operators use it to import live roles from company career pages. 🔎 Labor-market analysts use it to compare hiring patterns across multiple companies. 🤖 AI agent builders use it to feed fresh job data into matching, alerts, and enrichment workflows. ### Why use this actor? Lever pages are widely used by startups, scale-ups, and larger technology companies. Manual monitoring is slow when you need to watch dozens or hundreds of companies. This actor turns public job pages into a normalized dataset that is easy to export, filter, and connect to other tools. ### What data can you extract? | Field | Description | | --- | --- | | `companySlug` | Lever company slug supplied in the input | | `jobId` | Lever posting identifier | | `title` | Job title | | `hostedUrl` | Public Lever job page | | `applyUrl` | Application URL | | `location` | Job location category | | `department` | Department category | | `team` | Team category | | `workType` | Commitment or work type | | `workplaceType` | Remote, hybrid, or workplace category when available | | `country` | Country field when available | | `createdAt` | Posting creation time in ISO format | | `descriptionPlain` | Plain text description | | `descriptionHtml` | Optional HTML description | | `lists` | Structured sections from the posting | | `additionalPlain` | Additional plain text content | | `scrapedAt` | Time the actor saved the item | ### How much does it cost to scrape Lever jobs? The actor uses pay-per-event pricing. There is a small start charge per run and a per-job charge for each job posting saved to the dataset. For a typical company board with 100 jobs, the default target price is around $0.50 per 1,000 job postings before final tiered pricing is set on the Apify platform. You can keep costs predictable by setting a low `limit` while testing. ### How to use Lever Jobs Scraper 1. Open the actor on Apify. 2. Add one or more Lever company slugs. 3. Set a maximum number of job postings. 4. Optionally add department, team, location, or work-type filters. 5. Run the actor. 6. Download the dataset as JSON, CSV, Excel, XML, or HTML. ### Input example ```json { "companySlugs": ["spotify", "netflix"], "limit": 50, "departments": ["Engineering"], "locations": ["Remote"], "includeDescriptionHtml": false } ```` ### Input options `companySlugs` is required. Use the slug from the Lever job board URL. For `https://jobs.lever.co/spotify`, the slug is `spotify`. `limit` controls the maximum number of jobs saved across all companies. `departments` filters by Lever department category. `locations` filters by partial location text. `teams` filters by Lever team category. `workTypes` filters by commitment values such as Full-time or Internship. `includeDescriptionHtml` adds original HTML description fields when you need formatting. ### Output example ```json { "companySlug": "spotify", "jobId": "abc123", "title": "Data Engineer", "hostedUrl": "https://jobs.lever.co/spotify/...", "applyUrl": "https://jobs.lever.co/spotify/.../apply", "location": "New York", "team": "Platform", "department": "Engineering", "workType": "Full-time", "commitment": "Full-time", "createdAt": "2026-06-20T00:00:00.000Z", "descriptionPlain": "About the role...", "scrapedAt": "2026-06-20T05:00:00.000Z" } ``` ### Tips for best results ✅ Start with one company slug and a small limit. ✅ Use company slugs exactly as they appear in the Lever URL. ✅ Use location filters like `Remote`, `London`, or `New York` for broad matching. ✅ Leave filters empty if you want the full board. ✅ Enable HTML descriptions only when your workflow needs formatted text. ### Monitor Lever jobs for hiring signals Track new roles at target accounts, watch hiring by team or location, and turn Lever postings into recruiting, sales, and labor-market signals. Use `companySlug`, `team`, `department`, `workType`, URLs, and description fields to separate source-specific Lever data from generic job listings. ### Common use cases Track new roles at target accounts. Build a job-alert feed for specific companies. Monitor engineering hiring by location. Create company expansion signals for sales outreach. Collect clean job data for market maps. Feed job descriptions into an AI matching workflow. ### Export Lever jobs to Google Sheets, CRM, or API Connect the dataset to spreadsheets, CRMs, warehouses, or the Apify API to keep hiring dashboards and lead workflows current. ### Lever Jobs Scraper vs generic job scrapers This actor is built for Lever boards: it supports multi-company monitoring, Lever slugs, source URLs, category filters, hosted/apply URLs, and Lever-specific team, department, work-type, and description fields. ### Integrations Connect the dataset to Google Sheets for a live hiring tracker. Export CSV into a CRM to create account expansion alerts. Use Apify webhooks to trigger Slack notifications when a run finishes. Use Make or Zapier to route new jobs to downstream systems. Use the Apify API to schedule daily or weekly company monitoring. ### API usage #### Node.js ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('fetch_cat/lever-jobs-scraper').call({ companySlugs: ['spotify'], limit: 25 }); console.log(run.defaultDatasetId); ``` #### Python ```python from apify_client import ApifyClient client = ApifyClient('MY-APIFY-TOKEN') run = client.actor('fetch_cat/lever-jobs-scraper').call(run_input={ 'companySlugs': ['spotify'], 'limit': 25, }) print(run['defaultDatasetId']) ``` #### cURL ```bash curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~lever-jobs-scraper/runs?token=MY-APIFY-TOKEN' \ -H 'Content-Type: application/json' \ -d '{"companySlugs":["spotify"],"limit":25}' ``` ### MCP usage You can use this actor from Claude Desktop, Claude Code, or other MCP clients through Apify MCP. Use an MCP URL with the actor tool selected: `https://mcp.apify.com/?tools=fetch_cat/lever-jobs-scraper` Add it in Claude Code with: ```bash claude mcp add apify-lever-jobs --transport http "https://mcp.apify.com/?tools=fetch_cat/lever-jobs-scraper" ``` Claude Desktop JSON configuration example: ```json { "mcpServers": { "apify-lever-jobs": { "url": "https://mcp.apify.com/?tools=fetch_cat/lever-jobs-scraper" } } } ``` Example prompts: - "Run the Lever Jobs Scraper for spotify and summarize engineering roles." - "Check whether these target companies are hiring in London." - "Export the latest Lever jobs for my sales account list." ### Scheduling Schedule this actor daily, weekly, or monthly from Apify Console. For monitoring, use a small company list per run and keep `limit` aligned with your expected board sizes. Use webhooks when you want a downstream process to start as soon as the dataset is ready. ### Handling invalid or empty boards If a company slug is invalid, the actor logs the failure and records it in the `RUN-SUMMARY` key-value store record. If one slug fails but another succeeds, the run still completes and returns available jobs. If every supplied slug fails, the run fails so you can notice the input problem. If a valid company has no open jobs, the actor can finish with zero items. ### Data quality notes Lever company boards may use different department, team, and commitment values. Some postings may omit optional fields such as country or workplace type. Descriptions are returned as plain text by default. HTML fields can be enabled for workflows that preserve formatting. ### Legality This actor extracts publicly available job postings. You are responsible for using the data lawfully and respecting applicable terms, privacy rules, and data protection requirements. Do not use scraped data for spam, discrimination, or unlawful profiling. ### FAQ #### Can I scrape multiple Lever companies in one run? Yes. Add multiple values to `companySlugs` and set a limit that matches your expected volume. #### What is a Lever company slug? It is the part after `jobs.lever.co/` in a Lever board URL. For `https://jobs.lever.co/spotify`, use `spotify`. #### Why did I get zero results? The company may have no public roles, the filters may be too strict, or the slug may not be a Lever board slug. Check the run log and `RUN-SUMMARY` record for failed slugs. #### Can I include HTML job descriptions? Yes. Set `includeDescriptionHtml` to `true`. #### Can I use this as a Lever jobs API? Yes. Run the actor through the Apify API or client libraries and read structured Lever job records from the dataset. #### Can I monitor multiple Lever company boards on a schedule? Yes. Add multiple company slugs, set a practical `limit`, and attach an Apify schedule for daily or weekly monitoring. #### Can I use Lever job data with Apify MCP or Claude? Yes. Use the MCP URL above to call this actor from MCP-compatible tools such as Claude Desktop or Claude Code. #### What happens if a Lever company slug is invalid or has no open jobs? Invalid slugs are logged and summarized in `RUN-SUMMARY`; valid boards with no open roles can finish with zero items. ### Troubleshooting If a slug fails, try opening the corresponding Lever jobs page in a browser and confirm it exists. If filters remove too many rows, run once without filters and inspect the department, team, and location values in the dataset. If your automation needs every field, export JSON rather than CSV so nested `lists` stay intact. ### Related actors Explore related Apify actors from `fetch_cat` for company hiring, recruiting, and job-market workflows: - [Greenhouse Jobs Scraper](https://apify.com/fetch_cat/greenhouse-jobs-scraper) - [Workday Jobs Scraper](https://apify.com/fetch_cat/workday-jobs-scraper) - [Ashby Jobs Scraper](https://apify.com/fetch_cat/ashby-jobs-scraper) - [LinkedIn Jobs Scraper](https://apify.com/fetch_cat/linkedin-jobs-scraper) ### Changelog Initial version supports public Lever company job boards, multi-company inputs, global limits, category filters, optional HTML descriptions, and normalized job posting output. # Actor input Schema ## `companySlugs` (type: `array`): Lever company slugs from jobs.lever.co URLs. Example: use `spotify` for https://jobs.lever.co/spotify. You can also paste full Lever job board URLs. ## `limit` (type: `integer`): Maximum number of job postings to save across all company slugs. ## `departments` (type: `array`): Optional department filters. Values must match Lever category names such as Engineering, Finance, or Product. ## `locations` (type: `array`): Optional location filters. Matching is case-insensitive and allows partial matches such as `New York`, `Remote`, or `London`. ## `teams` (type: `array`): Optional team filters. Values must match Lever category names exactly, ignoring case. ## `workTypes` (type: `array`): Optional commitment filters such as Full-time, Part-time, Internship, or Contract. ## `includeDescriptionHtml` (type: `boolean`): Include original HTML description and additional fields in addition to plain text. ## Actor input object example ```json { "companySlugs": [ "spotify" ], "limit": 20, "departments": [], "locations": [], "teams": [], "workTypes": [], "includeDescriptionHtml": false } ``` # 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 = { "companySlugs": [ "spotify" ], "limit": 20, "departments": [], "locations": [], "teams": [], "workTypes": [], "includeDescriptionHtml": false }; // Run the Actor and wait for it to finish const run = await client.actor("fetch_cat/lever-jobs-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 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); }); // 📚 Want to learn more 📖? Go to → 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 = { "companySlugs": ["spotify"], "limit": 20, "departments": [], "locations": [], "teams": [], "workTypes": [], "includeDescriptionHtml": False, } # Run the Actor and wait for it to finish run = client.actor("fetch_cat/lever-jobs-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "companySlugs": [ "spotify" ], "limit": 20, "departments": [], "locations": [], "teams": [], "workTypes": [], "includeDescriptionHtml": false }' | apify call fetch_cat/lever-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fetch_cat/lever-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Lever Jobs Scraper for Hiring Signal Data", "description": "Export public Lever jobs with titles, teams, locations, URLs, descriptions, and timestamps for recruiting, sales signals, job boards, and hiring alerts.", "version": "0.1", "x-build-id": "plVVnL2PlPbidW1F8" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fetch_cat~lever-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fetch_cat-lever-jobs-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fetch_cat~lever-jobs-scraper/runs": { "post": { "operationId": "runs-sync-fetch_cat-lever-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fetch_cat~lever-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-fetch_cat-lever-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "companySlugs" ], "properties": { "companySlugs": { "title": "Lever company slugs", "minItems": 1, "type": "array", "description": "Lever company slugs from jobs.lever.co URLs. Example: use `spotify` for https://jobs.lever.co/spotify. You can also paste full Lever job board URLs.", "items": { "type": "string" } }, "limit": { "title": "Maximum job postings", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of job postings to save across all company slugs.", "default": 20 }, "departments": { "title": "Departments", "type": "array", "description": "Optional department filters. Values must match Lever category names such as Engineering, Finance, or Product.", "items": { "type": "string" } }, "locations": { "title": "Locations", "type": "array", "description": "Optional location filters. Matching is case-insensitive and allows partial matches such as `New York`, `Remote`, or `London`.", "items": { "type": "string" } }, "teams": { "title": "Teams", "type": "array", "description": "Optional team filters. Values must match Lever category names exactly, ignoring case.", "items": { "type": "string" } }, "workTypes": { "title": "Work types / commitments", "type": "array", "description": "Optional commitment filters such as Full-time, Part-time, Internship, or Contract.", "items": { "type": "string" } }, "includeDescriptionHtml": { "title": "Include HTML descriptions", "type": "boolean", "description": "Include original HTML description and additional fields in addition to plain text.", "default": false } } }, "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 } } } } } } } } } } ```