# SuccessFactors Jobs & Company Careers Scraper (`scrapers_lat/successfactors-jobs-scraper`) Actor
Scrape every open job from any company career site running on SAP SuccessFactors with title, department, location (city, state, country, remote), employment type, apply link, posted date, full description and the hiring company. Export to JSON, CSV or Excel.
- **URL**: https://apify.com/scrapers\_lat/successfactors-jobs-scraper.md
- **Developed by:** [Scrapers Lat](https://apify.com/scrapers_lat) (community)
- **Categories:** Jobs, Business, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $12.75 / 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.
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/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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
## SuccessFactors Jobs & Company Careers Scraper
> Extract every open job from any company career site running on SAP SuccessFactors, straight from its public listing, with title, location, employment type, apply link, posted date, full description and hiring company
Full descriptions and employment type
Any company on SuccessFactors
JSON / CSV / Excel output formats
No login no API key
### What you get
Point the scraper at one or more company career sites running on SAP SuccessFactors (for example
`https://jobs.sap.com`) and get every open role on that site as a structured record:
- **title**: the job title
- **company**: the hiring company name
- **location**: the parsed work location as `city`, `state`, `country` and `remote`
- **listingLocation**: the location label as shown on the listing
- **postalCode**: the postal code when set
- **employmentType**: full-time, part-time, contract and so on, when published
- **description**: the full job description as clean text
- **industry**: the job's industry when set
- **postedDate**: when the role was published
- **applyUrl**: the public job page and apply link
- **jobId**: the stable id for the posting
- **careerSite**: the career site the job came from
- **observedAt**: when this listing was last seen by the scraper
### Who is it for
| Use case | Who benefits |
|---|---|
| Track open roles at large employers for candidate outreach | Recruiters and staffing agencies |
| Read hiring signals to time sales and prospecting | Sales and revenue teams |
| Monitor competitor headcount and team growth | Market and competitive researchers |
| Build a live job board or careers aggregator feed | Job board and marketplace builders |
| Benchmark roles and locations across employers | Talent and labor market analysts |
### How to use it
1. Open a company's SuccessFactors career site and copy its home or search URL (for example `https://jobs.sap.com`).
2. Paste one or more sites into **Career site URLs**. Add one entry per company.
3. Optionally set a **Keyword** to restrict the search, and **Max Items** to cap the total.
4. Run it and export the results to JSON, CSV or Excel, or pull them through the API.
### Frequently Asked Questions
**Which sites does this work with?**
Company career sites powered by SAP SuccessFactors, which many large employers use for their public
job listings. Paste the career-site home or search URL and the scraper handles the rest.
**How many jobs can it return per site?**
It pages through every open role on the site, from a handful to thousands. Use Max Items to cap the
combined total when you only need a sample.
**Can I scrape several companies in one run?**
Yes. Add multiple career sites and the scraper collects jobs from each in turn, tagging every record
with its careerSite so you can tell them apart.
**Do I get the full job description?**
Yes, when Fetch full job details is on the scraper adds the complete description, employment type,
parsed city, state and country, posted date and company for each role. Turn it off for a faster,
lighter run that still returns title, location and apply link.
**What happens if a site URL is wrong?**
The scraper records an error row for that site with the reason and moves on to the next one, so one
bad entry never stops the run.
### Export, API and AI agents (x402 + MCP)
Export the scraped data to **JSON, CSV or Excel**, pull it as a **dataset** through the Apify **API**, or wire it into your app with **no code**. This web scraper and data extractor also works for bulk data extraction and scheduled runs.
For AI agents: this Actor is available on **x402**, Apify's agentic payment standard built with Coinbase. An AI agent can discover, pay for and run it on its own with a funded wallet and a single HTTP request: no account, no subscription, no API key and no human in the loop. It also runs as an **MCP** tool inside Claude, Cursor and other AI clients out of the box. Learn more about [x402 agentic payments on Apify](https://docs.apify.com/platform/integrations/x402).
### Related scrapers
Need data from the same space? Here are other scrapers we build and maintain:
- [Paylocity Jobs & Company Careers Scraper](https://apify.com/scrapers_lat/paylocity-jobs-scraper): Every open role from any company career board on Paylocity.
- [Breezy HR Jobs & Careers Scraper](https://apify.com/scrapers_lat/breezy-hr-jobs-scraper): Every open role from any company hiring on Breezy HR.
- [Greenhouse Job Board Listings Scraper](https://apify.com/scrapers_lat/greenhouse-jobs-scraper): Every open role from any company hiring on Greenhouse.
- [Ashby Jobs & Careers Scraper](https://apify.com/scrapers_lat/ashby-jobs-scraper): Job postings from any company career board on Ashby.
- [Indeed Jobs & Salary Scraper](https://apify.com/scrapers_lat/indeed-jobs-scraper): Job postings, companies and pay ranges from Indeed.
### More scrapers at scrapers.lat
This actor is built and maintained by [scrapers.lat](https://scrapers.lat), where we publish
scrapers for Latin American and US public platforms: real estate, jobs, e-commerce, company
registries and government data. Browse the full catalog, see live sample output for each one, or
ask us for a custom scraper at [scrapers.lat](https://scrapers.lat).
---
> This actor is an independent tool and has no affiliation with SAP or SuccessFactors. It only
> accesses data that is publicly available on company career sites. Use it in accordance with the
> relevant terms of service.
# Actor input Schema
## `maxJobs` (type: `integer`):
Maximum number of jobs to collect across all sites. Optional.
## `careerSites` (type: `array`):
One or more company career sites running on SAP SuccessFactors (for example https://jobs.sap.com). Paste the career-site home or search URL. Add one entry per company.
## `keyword` (type: `string`):
Optional. Restrict to jobs matching this search keyword (for example 'engineer', 'sales', 'data').
## `fetchDetails` (type: `boolean`):
Fetch each job's detail page to add the full description, employment type, parsed city / state / country, posted date and company. Turn off for a faster, lighter run.
## Actor input object example
```json
{
"maxJobs": 50,
"careerSites": [
"https://jobs.sap.com"
],
"fetchDetails": true
}
````
# 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 = {
"maxJobs": 50,
"careerSites": [
"https://jobs.sap.com"
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapers_lat/successfactors-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 = {
"maxJobs": 50,
"careerSites": ["https://jobs.sap.com"],
}
# Run the Actor and wait for it to finish
run = client.actor("scrapers_lat/successfactors-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 '{
"maxJobs": 50,
"careerSites": [
"https://jobs.sap.com"
]
}' |
apify call scrapers_lat/successfactors-jobs-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapers_lat/successfactors-jobs-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "SuccessFactors Jobs & Company Careers Scraper",
"description": "Scrape every open job from any company career site running on SAP SuccessFactors with title, department, location (city, state, country, remote), employment type, apply link, posted date, full description and the hiring company. Export to JSON, CSV or Excel.",
"version": "0.1",
"x-build-id": "OC1D0apKPS05saBzr"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapers_lat~successfactors-jobs-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapers_lat-successfactors-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapers_lat~successfactors-jobs-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapers_lat-successfactors-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapers_lat~successfactors-jobs-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapers_lat-successfactors-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"maxJobs": {
"title": "Max jobs",
"minimum": 1,
"maximum": 1000000,
"type": "integer",
"description": "Maximum number of jobs to collect across all sites. Optional."
},
"careerSites": {
"title": "Career site URLs",
"type": "array",
"description": "One or more company career sites running on SAP SuccessFactors (for example https://jobs.sap.com). Paste the career-site home or search URL. Add one entry per company.",
"items": {
"type": "string"
}
},
"keyword": {
"title": "Keyword",
"type": "string",
"description": "Optional. Restrict to jobs matching this search keyword (for example 'engineer', 'sales', 'data')."
},
"fetchDetails": {
"title": "Fetch full job details",
"type": "boolean",
"description": "Fetch each job's detail page to add the full description, employment type, parsed city / state / country, posted date and company. Turn off for a faster, lighter run.",
"default": true
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```