# Teamtailor Jobs Scraper - Public RSS Job Feeds (`benthepythondev/teamtailor-jobs-scraper`) Actor Scrape public Teamtailor career sites into structured job rows with titles, companies, locations, departments, remote status, descriptions and application links. - **URL**: https://apify.com/benthepythondev/teamtailor-jobs-scraper.md - **Developed by:** [Ben](https://apify.com/benthepythondev) (community) - **Categories:** Jobs, Automation, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## Teamtailor Jobs Scraper - Public RSS Job Feeds Collect current job openings from public Teamtailor career sites and turn them into structured, analysis-ready records. The Actor reads Teamtailor's documented public RSS feed, paginates through available vacancies, removes duplicate jobs, converts HTML descriptions to clean text, and saves one dataset item per opening. Use it to monitor companies that use Teamtailor, build a focused job board, create recruiting alerts, map hiring demand, or identify companies investing in particular departments. No Teamtailor account, browser session, API token, or proxy configuration is required for public career sites. ### What this Actor does Teamtailor powers branded career pages for companies across Europe and other markets. Those pages expose public job information through an RSS endpoint. A normal RSS reader can display the feed, but it does not provide a convenient workflow for combining several employers, filtering by hiring signal, exporting detailed location objects, or feeding the results into an automation. This Actor fills that gap. Paste one or more public Teamtailor career-site URLs and it will: 1. Convert each career URL to its public `jobs.rss` endpoint. 2. Fetch current vacancies directly over HTTP. 3. Paginate with Teamtailor's supported `offset` and `per_page` parameters. 4. Parse job, company, department, role, division, location and remote-work metadata. 5. Convert the public HTML description into clean plain text when requested. 6. Apply optional keyword, location, department and remote-work filters. 7. Deduplicate records by Teamtailor job ID or application URL. 8. Save the final rows to an Apify dataset for JSON, CSV, Excel, API or integration use. The default input requests only ten jobs, so scheduled tests are fast and inexpensive. Increase `maxResults` when you need a larger export. ### When to use it #### Recruitment market intelligence Track which employers are hiring for engineering, sales, support, operations or leadership roles. Department, role and division fields make it easier to group openings without relying only on title keywords. #### Hiring-intent lead generation An active vacancy is a useful business signal. Sales and recruiting teams can monitor target companies for new headcount, then combine the company name with a website or contact-enrichment workflow. The Actor returns public company and vacancy data; it does not invent contact details. #### Niche job boards Combine several Teamtailor career sites into one recurring dataset, filter for a profession or region, and publish only newly seen job IDs. This works well for country-specific, remote-work, startup or industry job feeds. #### Job alerts and automation Create an Apify task with fixed career sites and filters, schedule it daily, and send the output to Make, Zapier, n8n, Google Sheets, Airtable, Notion, Slack or your own webhook. Use `job_id` or `url` as the stable key when comparing runs. #### Workforce and location analysis Locations are returned as structured objects as well as a readable summary. This supports city, country and remote-work comparisons without losing the original Teamtailor metadata. ### Input | Field | Type | Description | |---|---|---| | `careerUrls` | array | Public Teamtailor career-site roots, jobs pages or `.rss` feed URLs. Up to 20 per run. | | `query` | string | Optional words that must all appear in the visible job data. | | `location` | string | Optional case-insensitive location substring. | | `department` | string | Optional case-insensitive department substring. | | `remoteOnly` | boolean | Keep jobs marked remote or hybrid by Teamtailor. | | `includeDescription` | boolean | Convert the public HTML job description to plain text. | | `maxResults` | integer | Maximum matching jobs saved across all supplied career sites. | You may paste any of these forms: ```text https://career.example.com https://career.example.com/jobs https://career.example.com/jobs.rss ```` The Actor normalizes them to the public feed and preserves any existing query parameters. #### Example input: one company ```json { "careerUrls": [ "https://career.teamtailor.com/jobs" ], "maxResults": 25, "includeDescription": true } ``` #### Example input: focused hiring monitor ```json { "careerUrls": [ "https://career.teamtailor.com/jobs" ], "query": "sales", "location": "London", "department": "Sales", "remoteOnly": false, "maxResults": 50 } ``` The keyword filter requires every supplied word to appear somewhere in the normalized title, description, company, department, role, division or location data. This avoids returning unrelated jobs merely because one broad term matched. ### Output fields Each vacancy is written as one default-dataset item with these fields: - `job_id`: Teamtailor's public global job identifier. - `title`: published job title. - `company`: career-site or employer name from the RSS channel. - `description`: clean plain-text description, or `null` when disabled. - `published_at`: publication timestamp normalized to UTC ISO 8601 when possible. - `url`: direct public job page or application URL. - `remote_status`: Teamtailor's published remote-work classification. - `locations`: structured location objects with name, address, ZIP code, city and country. - `location_text`: readable de-duplicated location summary. - `department`: public Teamtailor department. - `role`: public Teamtailor role. - `division`: public Teamtailor division. - `source`: constant value `teamtailor` for downstream routing. - `career_site_url`: public career-site home URL from the feed. - `source_feed`: normalized RSS feed URL used for the record. - `scraped_at`: UTC timestamp for the collection run. #### Example result ```json { "job_id": "https://career.teamtailor.com/jobs/1234567-account-executive", "title": "MidMarket Account Executive", "company": "Teamtailor", "description": "Join our sales team and help growing companies improve their hiring experience...", "published_at": "2026-07-10T08:30:00+00:00", "url": "https://career.teamtailor.com/jobs/1234567-account-executive", "remote_status": "Hybrid Remote", "locations": [ { "name": "London", "address": null, "zip": null, "city": "London", "country": "United Kingdom" } ], "location_text": "London", "department": "Sales", "role": "Account Executive", "division": null, "source": "teamtailor", "career_site_url": "https://career.teamtailor.com/", "source_feed": "https://career.teamtailor.com/jobs.rss", "scraped_at": "2026-07-13T15:00:00+00:00" } ``` Fields that are not published by a specific employer remain `null`. The Actor does not generate missing salaries, locations, departments or contact information. ### Pricing and cost control This Actor uses transparent pay-per-event pricing: - A small one-time Actor start event is charged when a run begins. - The primary `result` event costs **$0.0015 per job saved** to the default dataset. The default `maxResults` value is 10, which keeps a default run tightly bounded. Optional filters are applied before a row is saved and charged. A run that cannot find matching public jobs fails explicitly instead of reporting a misleading successful empty dataset. ### Data quality and reliability The engine uses Teamtailor's public RSS format rather than browser automation or fragile visual selectors. XML is parsed with a structured parser, descriptions are normalized with an HTML parser, pagination is bounded, and transient HTTP failures are retried with backoff. Records are deduplicated before they reach the dataset. The feed remains controlled by each employer. A company can remove a vacancy, change metadata, move to another recruiting platform, or make its career site private. If a feed no longer exists, the Actor reports a clear error rather than silently returning fabricated data. For repeat monitoring, keep each company's career URL in a saved task and compare `job_id` values between scheduled datasets. Treat jobs missing from a later feed as potentially closed, but confirm important status changes on the public job page. ### Responsible use This Actor reads publicly accessible job-listing metadata. You are responsible for respecting the career site's terms, applicable database and copyright rules, privacy law, and any requirements that apply to your downstream use. Do not use job data for spam, discriminatory profiling, or automated decisions about individuals. Keep attribution and links when republishing listings, and avoid redistributing full descriptions when you do not have permission. ### FAQ #### Do I need a Teamtailor API key? No. This Actor uses the public RSS feed documented for public Teamtailor career sites. It does not access private candidate, application or recruiter data. #### Does it support custom career domains? Yes. Supply the public custom domain. The Actor appends `/jobs.rss` unless the URL already points to a jobs page or RSS feed. #### Can I scrape several employers in one run? Yes. Add up to 20 career-site URLs. `maxResults` is the total output limit across the run, not a separate limit for every employer. #### Can I search Teamtailor globally by keyword? The Actor filters the feeds you provide; it does not claim to discover every Teamtailor customer on the internet. Build a monitored employer list, then apply `query`, `location` and `department` to those public feeds. #### Why did a filtered run return no rows? Every keyword must appear in the normalized public job data, and location and department filters are also exact substrings. Relax one filter, verify that the employer still has live jobs, and retry. #### Is remote work inferred from the description? No. `remoteOnly` relies on Teamtailor's explicit remote-status metadata. This avoids treating a casual mention of remote tools as a remote vacancy. #### How often should I schedule it? Daily is appropriate for most hiring monitors. Higher frequency is rarely necessary unless the employer publishes time-sensitive, high-volume openings. #### Can I export the data? Yes. Use Apify's JSON, JSONL, CSV, XML or Excel dataset exports, call the dataset API, or connect the Actor to supported automation platforms. #### What should I use as a unique key? Use `job_id`, with `url` as a fallback. The Actor applies the same rule internally when removing duplicates. #### How do I report a broken feed or missing field? Open an issue on the Actor page with the public career URL, the run ID and the field you expected. Do not include credentials or private candidate data. Support reports are reviewed promptly and fixes are verified against a live cloud dataset. ### You might also like - [ATS Jobs Aggregator](https://apify.com/benthepythondev/ats-jobs-aggregator) for combining several supported recruiting platforms. - [Greenhouse Jobs Scraper](https://apify.com/benthepythondev/greenhouse-jobs-scraper) for public Greenhouse job boards. - [Lever Jobs Scraper](https://apify.com/benthepythondev/lever-jobs-scraper) for public Lever postings. - [Workable Jobs Scraper](https://apify.com/benthepythondev/workable-jobs-scraper) for public Workable careers. - [Website Contact Extractor](https://apify.com/benthepythondev/website-contact-extractor) for enriching company websites after identifying hiring intent. If the Actor saves useful jobs for your workflow, please share an honest review on the Actor page. Reviews help other users understand which career sites and automations work well, and they help prioritize support for real production use cases. **Keywords:** Teamtailor scraper, Teamtailor jobs API, Teamtailor RSS feed, Teamtailor job board, ATS jobs scraper, career site scraper, recruitment data, hiring intent data, public job feed, job listings API, remote jobs data, company hiring monitor, job board automation, Apify jobs scraper. # Actor input Schema ## `careerUrls` (type: `array`): Public Teamtailor career-site or jobs-page URLs. Examples: https://career.teamtailor.com or https://career.teamtailor.com/jobs. The Actor converts each URL to its public jobs.rss feed. ## `query` (type: `string`): Optional words that must all appear in the job title, description, company, department, role, division or location. ## `location` (type: `string`): Optional case-insensitive location substring, such as London, Sweden or Remote. ## `department` (type: `string`): Optional department substring, such as Sales, Engineering or Customer Success. ## `remoteOnly` (type: `boolean`): Keep only jobs whose Teamtailor remote-status field indicates remote or hybrid work. ## `includeDescription` (type: `boolean`): Convert each public HTML job description to clean plain text. Disable for smaller datasets. ## `maxResults` (type: `integer`): Maximum number of matching jobs saved across all supplied career sites. ## Actor input object example ```json { "careerUrls": [ "https://career.teamtailor.com/jobs" ], "query": "", "location": "", "department": "", "remoteOnly": false, "includeDescription": true, "maxResults": 10 } ``` # Actor output Schema ## `results` (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 = { "careerUrls": [ "https://career.teamtailor.com/jobs" ], "query": "", "location": "", "department": "", "remoteOnly": false, "includeDescription": true, "maxResults": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("benthepythondev/teamtailor-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 = { "careerUrls": ["https://career.teamtailor.com/jobs"], "query": "", "location": "", "department": "", "remoteOnly": False, "includeDescription": True, "maxResults": 10, } # Run the Actor and wait for it to finish run = client.actor("benthepythondev/teamtailor-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 '{ "careerUrls": [ "https://career.teamtailor.com/jobs" ], "query": "", "location": "", "department": "", "remoteOnly": false, "includeDescription": true, "maxResults": 10 }' | apify call benthepythondev/teamtailor-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=benthepythondev/teamtailor-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Teamtailor Jobs Scraper - Public RSS Job Feeds", "description": "Scrape public Teamtailor career sites into structured job rows with titles, companies, locations, departments, remote status, descriptions and application links.", "version": "1.0", "x-build-id": "ErfV038I2scAuGVtR" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/benthepythondev~teamtailor-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-benthepythondev-teamtailor-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/benthepythondev~teamtailor-jobs-scraper/runs": { "post": { "operationId": "runs-sync-benthepythondev-teamtailor-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/benthepythondev~teamtailor-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-benthepythondev-teamtailor-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "careerUrls": { "title": "Teamtailor career-site URLs", "minItems": 1, "maxItems": 20, "type": "array", "description": "Public Teamtailor career-site or jobs-page URLs. Examples: https://career.teamtailor.com or https://career.teamtailor.com/jobs. The Actor converts each URL to its public jobs.rss feed.", "default": [ "https://career.teamtailor.com/jobs" ], "items": { "type": "string" } }, "query": { "title": "Keywords", "type": "string", "description": "Optional words that must all appear in the job title, description, company, department, role, division or location.", "default": "" }, "location": { "title": "Location filter", "type": "string", "description": "Optional case-insensitive location substring, such as London, Sweden or Remote.", "default": "" }, "department": { "title": "Department filter", "type": "string", "description": "Optional department substring, such as Sales, Engineering or Customer Success.", "default": "" }, "remoteOnly": { "title": "Remote or hybrid jobs only", "type": "boolean", "description": "Keep only jobs whose Teamtailor remote-status field indicates remote or hybrid work.", "default": false }, "includeDescription": { "title": "Include job descriptions", "type": "boolean", "description": "Convert each public HTML job description to clean plain text. Disable for smaller datasets.", "default": true }, "maxResults": { "title": "Maximum jobs", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of matching jobs saved across all supplied career sites.", "default": 10 } } }, "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 } } } } } } } } } } ```