# Jobs by Technology — SAP, Snowflake, Kubernetes & more (`nivult/jobs-by-technology`) Actor

Live job postings filtered by the technologies mentioned in the text — SAP, Snowflake, Kubernetes, Salesforce and thousands more. Refreshed daily, every field with its source.

- **URL**: https://apify.com/nivult/jobs-by-technology.md
- **Developed by:** [Nivult](https://apify.com/nivult) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

![Who is hiring for Snowflake today — Nivult](https://raw.githubusercontent.com/granno-dev/nivult-engine/main/apify/assets/copertina-tecnologie.png)

### What does "Jobs by Technology" do?

Type a technology — **SAP, Snowflake, Kubernetes, Salesforce, anything** — and get every live job posting that mentions it **in the text of the ad**, not just in the title. Read daily from the career systems of tens of thousands of employers, worldwide.

For sales teams it is a lead list ("who is implementing Snowflake right now?"), for recruiters a talent map, for analysts a demand signal — measured from what employers actually write.

- 🧩 **Technology matching in the full text** — the stack the posting really asks for
- 🌍 **Country** — 240+ countries and territories
- 🎯 **Seniority & workplace** — intern to head, remote / hybrid / on site
- 🗓️ **Posted-after date** — only what is fresh
- 🏢 **Company mode** — the employers behind the postings, with industry and size

Every field carries **field-level provenance**: the row says where each value came from, so you can audit what you buy.

#### Not a scraper — a maintained index

Scrape-on-demand actors ask you for career-site URLs and minutes of your
patience, then hand you raw rows. **This dataset asks for nothing but
filters** — the reading already happened today, whether you run us or not.

| | Scrape-on-demand | **Nivult Dataset API** |
|---|---|---|
| You supply | URLs you must know | nothing — just filters |
| Answer in | minutes | **seconds** |
| Closed postings | stay forever | **verified closed**, daily |
| Enrichment | raw title + link | seniority, workplace, language, skills |
| Provenance | none | **field-level, on every row** |

![How it works: you set filters, the index refreshes daily, you get clean rows in seconds](https://raw.githubusercontent.com/granno-dev/nivult-engine/main/apify/assets/diagramma-tecnologie.png)

### How to use it

1. Type the technology (e.g. `Snowflake`) and set filters if you want.
2. Run it, then download JSON, CSV or Excel — or read the dataset through the Apify API.
3. For a standing feed of a technology every morning, ask about the daily feed (link on this page).

### How much does it cost?

**$3 per 1,000 rows received** — nothing for empty filters, nothing upfront. Apify's free plan covers your first hundreds of rows.

Why a row here costs more than a raw scrape: a raw row is a title and a link that may be dead by tonight. Ours is an **enriched, verified record** — classified, provenance-stamped, and closed out of the index the day it leaves the source. You are not paying for a scrape; you are paying for the maintenance.

### What does the output look like?

A real row from a Snowflake-mentioning posting (verbatim — the skills list is long because it is measured from the whole text):

```json
{
  "title": "Delivery Manager - Data Analytics Spread & Commissions",
  "company": "Careers Allegisgroup",
  "ats": "icims",
  "country": "US",
  "city": "Hanover",
  "skills": ["python", "sql", "aws", "azure", "gcp", "etl", "scrum", "agile", "project management", "warehouse", "snowflake", "unstructured data", "use logical reasoning"],
  "salary_estimate_median": 147500,
  "salary_estimate_currency": "USD",
  "salary_is_estimate": true,
  "posted_at": "2026-10-06",
  "url": "https://careers-allegisgroup.icims.com/jobs/2384/delivery-manager---data-analytics-spread-%26-commissions/job"
}
```

### Explore the Nivult family

- **[Job Postings Dataset — the full index](https://apify.com/nivult/global-job-postings)** — every ATS, every filter, company mode
- **[Workday Jobs Dataset](https://apify.com/nivult/workday-jobs-dataset)** — every Workday career site, daily
- **[Greenhouse Jobs Dataset](https://apify.com/nivult/greenhouse-jobs-dataset)** — every Greenhouse board, daily
- **[Jobs by Technology](https://apify.com/nivult/jobs-by-technology)** — postings matched by the stack in the text

### FAQ

**How do you know which technologies a posting asks for?**
We read the full text of the ad at the source and measure the stack it mentions — a posting that says "SAP" in the body counts even if the title doesn't say it.

**How fresh is the data?**
Daily. New postings land within 24 hours of appearing on the employer's career system.

**Which technologies are covered?**
Anything employers write — mainstream clouds and databases, ERP, CRM, data tools, languages. If it appears in postings, it is filterable.

**Is this legal?**
We read public postings on the employer's own site, respect robots directives and rate limits, and honor removal requests.

# Actor input Schema

## `tipo` (type: `string`):

Job postings or enriched company records

## `country` (type: `string`):

e.g. IT, DE, US — leave empty for worldwide

## `technology` (type: `string`):

e.g. SAP, Snowflake, Kubernetes — postings mentioning it in the text

## `q` (type: `string`):

free text in title and description

## `seniority` (type: `string`):

Filter by seniority level (optional)

## `remote` (type: `string`):

Filter by workplace type (optional)

## `dal` (type: `string`):

ISO date, e.g. 2026-10-01 — only fresher postings

## `limite` (type: `integer`):

1–10,000 (for bigger slices ask about the daily full export)

## Actor input object example

```json
{
  "tipo": "jobs",
  "seniority": "",
  "remote": "",
  "limite": 100
}
```

# Actor output Schema

## `results` (type: `string`):

The records matching your filters, in the default dataset — view them as a table or download as JSON, CSV, Excel.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("nivult/jobs-by-technology").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("nivult/jobs-by-technology").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call nivult/jobs-by-technology --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,nivult/jobs-by-technology"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/6YDrPdRfyoF4UAhF0/builds/tvBs76knXmKn4KBKz/openapi.json