Lever Job Scraper — Clean Schema + Seniority + Remote Type

For talent intelligence and job aggregation teams that scrape Spotify, GitHub, Netflix, Lyft, Figma — and need all office locations per posting, not just the primary.

Pay per result — $1.50 / 1,000 jobs. No API key. No proxy. Official Lever API — no bans.

Extract job postings from any Lever-powered career page — Spotify, Netflix, GitHub, Lyft, Figma, Brex, and 5,000+ more companies. Uses Lever's official public API: zero auth, zero proxy cost, zero bans.

What makes this scraper better?

Most Lever scrapers return raw API fields with minimal processing. This one adds:

Edge	What it means
Canonical seniority	Inferred from title: executive / vp / director / manager / principal / staff / lead / senior / intern / entry / mid
Canonical remote_type	remote / hybrid / onsite — from workplaceType first, location text fallback
Full merged descriptions	All Lever sub-sections merged: intro + body + bullet lists + additional info
Salary extraction	Parsed from salaryDescription when the company populates it
allLocations	Multi-location postings include all posting locations, not just the primary
parse_confidence	Machine-readable quality score per record (0.0–1.0) + warnings list
global_id	lever:<company>:<job_id> — stable deduplication key across runs
Clean, flat schema	Predictable column set every run — no surprise null keys

Input

{
  "companies": ["spotify", "github", "netflix"],
  "titleKeyword": "engineer",
  "locationKeyword": "New York",
  "remoteOnly": false,
  "includeDescriptions": true,
  "maxJobsPerCompany": 50,
  "maxTotalJobs": 0
}

How to find a company slug: Go to jobs.lever.co/<slug> — the slug is the part after lever.co/. Example: jobs.lever.co/spotify → slug is spotify.

Output schema

{
  "company":          "spotify",
  "title":            "Senior Software Engineer",
  "location":         "New York, NY",
  "all_locations":    "New York, NY, San Francisco, CA",
  "remote_type":      "hybrid",
  "seniority":        "senior",
  "department":       "Engineering",
  "team":             "Platform",
  "employment_type":  "Full-time",
  "salary":           "$150,000 – $200,000 USD",
  "url":              "https://jobs.lever.co/spotify/abc123",
  "apply_url":        "https://jobs.lever.co/spotify/abc123/apply",
  "posted_at":        "2024-01-15T08:30:00+00:00",
  "job_id":           "abc123",
  "global_id":        "lever:spotify:abc123",
  "description_text": "We are looking for…",
  "description_html": "<p>We are looking for…</p>",
  "parse_confidence": 1.0,
  "warnings":         []
}

Use cases

• AI job-matching pipelines — clean, flat schema feeds LLMs and vector DBs
• Talent intelligence — track competitor hiring signals in real time
• Job aggregator sites — populate boards with fresh postings
• Recruitment research — analyze tech hiring trends, seniority distributions
• Sales prospecting — identify companies actively hiring in specific roles

Pricing

Pay-per-result PPE model: $1.50 / 1,000 jobs ($0.0015 per record).

Worked example: 5 companies × 50 jobs = 250 results = $0.38. 20 companies × 100 jobs = 2,000 results = $3.00.

FAQ

Do I need an API key or proxy? No. Lever's public API (api.lever.co/v0/postings/<slug>) is open — no auth, no proxy cost, no bans.

What output formats are available? JSON, JSONL, CSV, and Excel via the Apify dataset export, plus the Apify REST API.

Can I schedule daily runs? Yes — use Apify Scheduler. Each run returns the current open jobs; use global_id (lever:<company>:<job_id>) as a stable key for deduplication.

What if a company returns 0 jobs or the slug is wrong? The actor logs a warning, records the slug in failedDetails, and continues with the remaining companies — no crash, no broken run.

Integrations

Built for talent-intelligence and job-aggregation teams tracking open roles with seniority, remote type, and salary across Lever boards — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

Is it legal?

Yes. We query Lever's official public API (api.lever.co/v0/postings/<slug>?mode=json), which is publicly accessible without authentication. No personal data beyond what companies choose to publish publicly.

Competitor comparison

Feature	This actor	satish5813/lever-jobs-scraper	bytepulselabs/lever-job-scraper
Seniority field	✅ (11 levels)	❌	❌
Canonical remote_type	✅	✅ raw field	partial
Merged descriptions (all sections)	✅	partial	partial
parse_confidence per record	✅	❌	❌
all_locations (multi-location postings)	✅	❌	❌
global_id for deduplication	✅	❌	❌
Title keyword filter	✅	✅	❌
Location keyword filter	✅	✅	❌
Remote-only filter	✅	❌	❌
maxTotalJobs cap (billing safety)	✅	❌	❌
Official API (no DOM scraping)	✅	✅	✅
Price	$1.50/1k	varies	varies

all_locations is unique to this actor in the cluster: multi-location Lever postings include every office, not just the primary posting location. Essential for global talent intelligence.

parse_confidence (0.0–1.0) and warnings in every record — deductions for missing job_id (0.50), title (0.30), url (0.10), location (0.05), posted_at (0.05), description (0.05).

Use with AI agents (MCP)

This actor is MCP-compatible. Use it as a data source in n8n, Make, or any LLM agent pipeline.

https://mcp.apify.com/?tools=bovi/lever-job-scraper

The flat schema with global_id (lever:<company>:<job_id>) and all_locations is designed for LLM pipelines, vector databases, and n8n/Make job-matching workflows. Need to cover Greenhouse, Ashby, Recruitee, SmartRecruiters and Personio too? Use the flagship Multi-ATS Job Scraper — all 6 ATS in one unified schema.