Jobs by Technology — SAP, Snowflake, Kubernetes & more

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 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):

{
  "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 — every ATS, every filter, company mode
• Workday Jobs Dataset — every Workday career site, daily
• Greenhouse Jobs Dataset — every Greenhouse board, daily
• 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.