India Tech Hiring Signals — Instahyre Jobs & Company Velocity 🇮🇳

foXLabs hiring series: LinkedIn Hiring Signals · Company Hiring Signals (any ATS) · LinkedIn Jobs · Greenhouse · Lever · Ashby · Workday · SmartRecruiters · Personio · Teamtailor · India firmographics: Indian Company Data foXLabs India series: Company registry · Government tenders · NSE filings · IndiaMART suppliers

🎉 Turn Instahyre's public job board into a hiring-velocity signal for Indian tech companies — no login, no API key, one row per employer with open roles, new roles this week and in your window, function and skill mix, headcount bucket and founded year. Or one PII-free row per listing. Built for B2B sales and go-to-market teams selling into Indian tech, and for VC and analyst teams tracking which startups are scaling.

🔍 What is India Tech Hiring Signals — and when should you use it?

Instahyre is an Indian tech-hiring marketplace where employers — from 10-person startups to Accenture and Amazon — post open roles. This actor reads its public job search and turns it into company-level hiring signals: for every employer that matches your filters it counts the open roles, how many of them appeared in the last 7 days and in your chosen window, which functions and skills they hire for, and the employer's headcount bucket and founded year. Switch to jobs mode for one clean row per listing instead.

Use it when you need: a list of Indian tech companies that are hiring right now (for outbound or account prioritisation); the hiring velocity of a fixed watch list of companies, run weekly; a read on which startups in a city, function or industry are scaling; or PII-free job-posting data for market analysis.

Use something else when: you need recruiter or hiring-manager contacts (not collected — by design), salaries (Instahyre does not publish them), or companies that do not hire on Instahyre — use LinkedIn Hiring Signals or Company Hiring Signals (any ATS). For registry firmographics (CIN, directors, financials) pair it with Indian Company Data.

🤖 Use with AI agents

Already on the Apify MCP server? Ask for this Actor by name: foxlabs/india-tech-hiring-signals.

Your agent can pay for its own runs. This Actor is pay-per-event with agentic payments, so an agent can discover it, run it and settle the bill over x402 (USDC on Base) or Skyfire — no Apify account or API token of its own. Billing is the same either way: per delivered company or job row, never for summary or error rows.

Otherwise paste this into Claude, ChatGPT, Cursor or any MCP-enabled assistant:

I want hiring signals for Indian tech companies from Instahyre using the Apify Actor
`foxlabs/india-tech-hiring-signals`.

Input: `mode` is "companies" (one row per employer with open roles and new roles in the last
7 days / last N weeks) or "jobs" (one row per listing). Filters: `locations` (e.g. "Bangalore"),
`jobFunctions` (e.g. "category:software-engineering"), `companySize` ("small" | "medium" | "large"),
`companies` (a watch list of employer names), `skills`, `industryTypes`, `experienceYears`.
`weeksWindow` (1-8) sets the velocity window; `maxResults` caps the rows.

Start with:
{"mode":"companies","locations":["Bangalore"],"jobFunctions":["category:software-engineering"],"companySize":"medium","weeksWindow":4,"maxResults":200}

Ask me which city, function or companies to track, run the Actor, then rank the companies
by newJobsInWindow and summarise the top ones as a table.

Things you can ask your agent for:

• "Which 50–200-person software companies in Bangalore opened the most engineering roles in the last four weeks?"
• "Track Razorpay and Zepto every Monday and tell me whose hiring is speeding up."
• "Which banking and fintech employers are hiring data and ML people right now?"

The machine-readable API, MCP config and OpenAPI definition live at apify.com/foxlabs/india-tech-hiring-signals.md.

📋 Overview

Everything you need to turn Instahyre's public job board into a clean hiring-velocity table — in one actor, with no login, cookies or API key.

Why teams pick this actor:

• ✅ Company-first, not another job dump — one row per employer with open roles, new roles in the last 7 days and in your window, top functions, top skills and sample titles.
• 📅 Posting dates Instahyre's search doesn't show — resolved from Instahyre's own job sitemap; accuracy measured against each job page's datePosted (see How to read the numbers).
• 🔒 PII-free by design — recruiter names, designations and profile photos never reach your dataset: the default path never requests them, and with includeDescriptions the detail record is reduced on arrival to description, experience, category, functions and the internship/active flags.
• 🎯 Filters that match the site — cities, 107 job functions in 19 categories, 74 industries, company size, skills, experience, and a company watch list.
• 🧮 Complete counts — companies mode scans the whole filtered set, split so every part fits Instahyre's 10,000-result window (a part that still exceeds it is read up to the window and flagged in the log), and de-duplicates by job ID; maxResults only caps the output.
• 💰 Pay only for results — summary and error rows are never billed.
• 🤖 Agent-ready — MCP + x402 agentic payments.

✨ Features

• 🏢 Companies mode (default) — hiring velocity per employer: activeJobs, newJobsLast7Days, newJobsInWindow, topFunctions, topSkills, sampleTitles, headcount bucket, founded year, tagline, Instahyre company page.
• 📄 Jobs mode — one row per listing: title, company, locations, skill tags, category/functions, job type, posting date, public URL; optional plain-text description and required experience.
• 👀 Watch lists — track named companies; a misspelled name is reported and skipped, the rest of the list still runs.
• 🕳️ Honest empty results — a valid filter that matches nothing returns one SUMMARY row that says so and suggests what to change; the run still succeeds.
• 🐢 Rate-limit aware — when Instahyre answers HTTP 429, every worker pauses and the run slows down; each pause is counted in the run's SUMMARY record.

🎬 Quick Start

curl -X POST "https://api.apify.com/v2/acts/foxlabs~india-tech-hiring-signals/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"mode":"companies","locations":["Bangalore"],"jobFunctions":["category:software-engineering"],"companySize":"medium","weeksWindow":4,"maxResults":200}'

The run-sync endpoint waits for the run and returns the rows. In a local run without a proxy this input took 117 s and 43 requests and returned 200 company rows (run-a3-prefill, 2026-09-10); with the default Apify Proxy on the platform it has not been timed yet.

🚀 Getting Started (3 steps)

1. Pick the output — companies for hiring velocity per employer, jobs for one row per listing.
2. Narrow the market — a city, a function or category, a company size, skills or industries — or a watch list of company names.
3. Run and export — JSON, CSV or Excel from the dataset; schedule it weekly for a time series.

📥 Input

{"mode":"companies","locations":["Bangalore"],"jobFunctions":["category:software-engineering"],"companySize":"medium","weeksWindow":4,"maxResults":200}

Field	Type	Description
mode	string	companies (default) — one row per employer; jobs — one row per listing.
locations	array	City names as Instahyre spells them: Bangalore, Gurgaon, Hyderabad, Pune, Mumbai, Chennai, Noida, Delhi, Work From Home. Several = OR. An unknown name stops the run with a clear error.
jobFunctions	array	Whole categories (category:software-engineering) or single functions (function:backend-development) — the form lists all 19 categories and 107 functions. Several = OR.
skills	array	Skill tags as they appear on listings (Python, React.js, Machine Learning). Case does not matter.
companies	array	Watch list of employer names as shown on Instahyre (Razorpay, Zepto). Case does not matter.
companySize	string	any (default), small (up to 50 employees), medium (50–200), large (200+) — Instahyre's own size classes.
industryTypes	array	Employer industries as Instahyre classifies them, e.g. banking-financial-services, computer-software-it-internet.
experienceYears	integer	Keeps roles whose required experience range covers this many years (3 → e.g. 2–5 years).
weeksWindow	integer	Velocity window in weeks for newJobsInWindow, 1–8 (default 4).
maxResults	integer	Companies mode: employer rows to emit, best velocity first. Jobs mode: listings. 0 = no limit (default 500).
includeDescriptions	boolean	Jobs mode only: adds the plain-text description, required experience and exact functions (one extra request per job).
requestDelayMs	integer	Pause after every request, per worker (default 600).
maxConcurrency	integer	Requests in flight, 1–3 (default 2).
proxyConfiguration	object	Apify Proxy (default on).

Leave every filter empty — for example an API call with {} — and the actor scans every open role on Instahyre (13,386–13,610 when we measured on 2026-09-10), which takes several hundred requests. Start with a city and a function, as in the example above.

📤 Output

Companies mode — one row per employer (default)

Rows are sorted by newJobsInWindow, then newJobsLast7Days, then activeJobs; maxResults keeps the top of that list. Fill rates measured on the prefilled example input (local run run-a3-prefill, 200 rows, 2026-09-10).

Field	Description	Filled
companyName	Employer name as shown on Instahyre	100%
instahyreEmployerId	Instahyre's employer ID — the stable join key across runs	100%
tagline	The employer's one-line tagline on Instahyre	100%
about	Instahyre's short company description	100%
foundedYear	Founding year as listed on Instahyre; Instahyre's 1900 placeholder is returned as null	98% (5 of 297 employers in the final test runs carried the placeholder)
headcountBucket	Instahyre's headcount bucket: 0-10, 10-50, 50-200, 200-500, 500-1000, 1000+	100%
companySizeClass	small / medium / large, derived from headcountBucket	100%
instahyreCompanyUrl	The employer's Instahyre careers page	100%
locations	Cities of its matching open roles, most frequent first	100%
activeJobs	Open roles matching your filters	100%
newJobsLast7Days	Of those, roles posted in the last 7 days (today included)	100%
newJobsInWindow	Roles posted in the last weeksWindow weeks	100%
weeksWindow	The window you asked for, echoed for time series	100%
undatedJobs	Open roles without a resolved posting date — posted before the date horizon, or all of them if the sitemap could not be read (then the velocity counts are null)	100%
earliestPostedAt / lastPostedAt	Oldest and newest posting date among its dated open roles (ISO)	40.5% (81/200) — see The date horizon
topFunctions	Up to 10 {function, count} — the function mix of its open roles	100%
topSkills	Up to 10 {skill, count} from the listings' skill tags (case-merged)	100%
sampleTitles	Up to 5 titles, newest first	100%
source, scrapedAt	Instahyre; run timestamp (ISO)	100%

Real row from run-a3-prefill:

{
  "companyName": "NuPlay AI",
  "instahyreEmployerId": 49316,
  "tagline": "AI agents that get better on the job",
  "about": "NuPlay AI is a GenAI company building self-improving autonomous AI agents that automate customer engagement and complex enterprise workflows through voice, chat, and seamless business-system integrations.",
  "foundedYear": 2024,
  "headcountBucket": "50-200",
  "companySizeClass": "medium",
  "instahyreCompanyUrl": "https://www.instahyre.com/jobs-at-nuplay-ai/",
  "locations": [
    "Bangalore"
  ],
  "activeJobs": 17,
  "newJobsLast7Days": 2,
  "newJobsInWindow": 7,
  "weeksWindow": 4,
  "undatedJobs": 6,
  "earliestPostedAt": "2026-08-07",
  "lastPostedAt": "2026-09-10",
  "topFunctions": [
    {
      "function": "Backend Development",
      "count": 9
    },
    {
      "function": "Full-Stack Development",
      "count": 9
    },
    {
      "function": "Other Software Development",
      "count": 4
    },
    {
      "function": "Software Testing / QA / SDET",
      "count": 4
    },
    {
      "function": "Engineering Management",
      "count": 3
    },
    {
      "function": "Frontend Development",
      "count": 3
    },
    {
      "function": "Data Engineering / DWH / ETL",
      "count": 1
    }
  ],
  "topSkills": [
    {
      "skill": "AWS",
      "count": 10
    },
    {
      "skill": "Python",
      "count": 10
    },
    {
      "skill": "Azure",
      "count": 9
    },
    {
      "skill": "GCP",
      "count": 9
    },
    {
      "skill": "JavaScript",
      "count": 5
    },
    {
      "skill": "Kubernetes",
      "count": 5
    },
    {
      "skill": "Next.js",
      "count": 5
    },
    {
      "skill": "Node.js",
      "count": 5
    },
    {
      "skill": "React",
      "count": 5
    },
    {
      "skill": "Cypress",
      "count": 4
    }
  ],
  "sampleTitles": [
    "Software Engineer (Backend)",
    "QA / SDET Engineer",
    "Machine Learning Engineer",
    "QA Engineer",
    "QA Engineer"
  ],
  "source": "Instahyre",
  "scrapedAt": "2026-09-10T14:17:54.213Z"
}

Jobs mode — one row per listing

Fill rates measured on {"mode":"jobs","locations":["Bangalore"],"skills":["python"],"maxResults":100} (local run run-b-jobs-python, 100 rows) and, for the detail fields, on run-f-jobs-descriptions (includeDescriptions: true).

Field	Description	Filled
jobId	Instahyre job ID — unique per row	100%
title	Job title	100%
companyName, instahyreEmployerId, instahyreCompanyUrl	The employer, as in companies mode	100%
locations	Cities of the role	100%
keywords	Skill tags on the listing (average 6.4 per row)	100%
jobCategory	Category the job was found under (exact from the detail record with includeDescriptions)	100% in run-b-jobs-python; empty in watch-list runs unless includeDescriptions is on
jobFunctions	Functions — filled when you filter by function (without a watch list) or turn on includeDescriptions	0% in run-b-jobs-python (no function filter); 100% (5/5) in run-f-jobs-descriptions
jobType	full-time or internship	100%
experienceMinYears / experienceMaxYears	Required experience — includeDescriptions only	100% (5/5) in run-f-jobs-descriptions; empty otherwise
headcountBucket, companySizeClass, foundedYear	Employer firmographics	100%
publicUrl	The public job page on instahyre.com	100%
postedAt	Posting date (ISO) — see How to read the numbers	43.0% (43/100) — older roles predate the horizon
postedAtSource	sitemap-lastmod, or id-newer-than-sitemap for roles newer than the sitemap (dated to the run day)	same as postedAt
description	Plain-text description — includeDescriptions only	100% (5/5) in run-f-jobs-descriptions; field absent otherwise
source, scrapedAt	Instahyre; run timestamp	100%

Real row from run-b-jobs-python:

{
  "jobId": 442436,
  "title": "Ai Engineer",
  "companyName": "Altimetrik",
  "instahyreEmployerId": 2292,
  "instahyreCompanyUrl": "https://www.instahyre.com/jobs-at-altimetrik/",
  "locations": [
    "Bangalore",
    "Chennai",
    "Pune"
  ],
  "keywords": [
    "Python",
    "Machine Learning",
    "TensorFlow",
    "LLMs",
    "PyTorch"
  ],
  "jobCategory": "Software Engineering",
  "jobFunctions": null,
  "jobType": "full-time",
  "experienceMinYears": null,
  "experienceMaxYears": null,
  "headcountBucket": "1000+",
  "companySizeClass": "large",
  "foundedYear": 2012,
  "publicUrl": "https://www.instahyre.com/job-442436-ai-engineer-at-altimetrik-bangalore-chennai-pune/",
  "postedAt": "2026-09-09",
  "postedAtSource": "sitemap-lastmod",
  "source": "Instahyre",
  "scrapedAt": "2026-09-10T14:08:24.226Z"
}

Empty or rejected runs — one SUMMARY row

A valid filter that matches nothing does not end silently: the run succeeds with one SUMMARY row (never billed) that names the filters and suggests what to relax. A value Instahyre rejects (for example an unknown city) stops the run with the same kind of row and a clear error. Real row from run-e-valid-zero:

{
  "type": "SUMMARY",
  "status": "empty",
  "message": "Instahyre returned no jobs for: locations=Bangalore, skills=Python, companySize=small, experienceYears=25.",
  "hint": "Locations are matched as Instahyre spells them — common ones: Bangalore, Gurgaon, Hyderabad, Work From Home, Pune, Mumbai, Chennai, Noida, Delhi. Skills match the listing's skill tags, e.g. \"Python\", \"React.js\", \"Data Structures\". experienceYears keeps only roles whose experience range covers that value.",
  "cells": [
    {
      "label": "all functions",
      "total": 0
    }
  ],
  "warnings": [],
  "source": "Instahyre",
  "scrapedAt": "2026-09-10T14:22:35.610Z"
}

How to read the numbers

• Posting dates. Instahyre's search does not return dates. The actor reads Instahyre's own job sitemap (one request per 1,000 jobs) and dates each job by the earliest lastmod among it and every newer job, which corrects most later edits. On 2026-09-10 we checked 10 jobs posted between 13 Aug and 10 Sep against the datePosted on their own job pages: 10 of 10 exact (run run-b-jobs-python; 2 of them were newer than the sitemap and correctly dated to the run day). A second sample of 12 job pages saved earlier that day, 7 of them edited after posting, matched 11 of 12 — the miss was one day late. In these 22 checks the date was never early.
• The date horizon. Dates are resolved back to your window plus two weeks (with the default 4-week window it reached back to 2026-07-24 in run-a3-prefill). Older open roles are counted in activeJobs and undatedJobs but can never be "new".
• Velocity counts listed roles. A role that opened and closed inside the window is no longer listed, so it is not counted.
• Function mix. With a function or category filter, topFunctions is exact per function. Without one it is at category level. For watch-list rows it is Instahyre's own function breakdown for that employer, which lists its top 4 functions.
• Size classes. Instahyre's companySize filter uses its own classification; for 3 of 200 employers in run-a3-prefill it disagreed with the employer's headcountBucket (for example Locus.sh, 200-500, returned under medium). The row always shows the employer's bucket.
• foundedYear is Instahyre's value, except Instahyre's 1900 placeholder, which is returned as null. 5 of the 297 employers in the final test runs carried it — all long-established groups such as Taylor & Francis Group, Aditya Birla Group and MUFG.
• Jobs mode with maxResults stops as soon as it has enough listings, scanning tech categories first (Software Engineering, Data Science & Analytics, IT Operations, …), then returns them newest first — the newest N listings of that scan, not necessarily of all of Instahyre.

💼 Use cases

1. GTM lead lists — sell to companies while they hire. A company opening five backend roles this month is buying developer tooling, cloud and recruiting services. Input: a city + function + company size (the prefilled example input). Output: employers ranked by new roles in the window, with headcount bucket, founded year and sample titles. Use: a prioritised account list for outbound, refreshed weekly.

2. VC and analyst signals — spot who is scaling. Hiring velocity is one of the earliest public signs that a startup raised money or found traction. Input: a watch list of portfolio or target companies, scheduled weekly. Output: one row per company with open roles and new roles per window. Use: a company × week time series — flag accelerations and freezes before the press release.

3. Talent-market mapping — who competes for your hires. See which employers hire for the same skills in the same city. Input: skills + locations, jobs or companies mode. Output: listings or employers with their skill mix. Use: salary benchmarking lists, employer-branding targets, competitive hiring maps.

🔗 Integration

JavaScript / Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('foxlabs/india-tech-hiring-signals').call({"mode":"companies","locations":["Bangalore"],"jobFunctions":["category:software-engineering"],"companySize":"medium","weeksWindow":4,"maxResults":200});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items[0]);

Python

from apify_client import ApifyClient
client = ApifyClient('YOUR_TOKEN')
run = client.actor('foxlabs/india-tech-hiring-signals').call(run_input={"mode":"companies","companies":["Razorpay","Zepto"],"weeksWindow":4})
for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item['companyName'], item['activeJobs'], item['newJobsInWindow'])

Automation (n8n / Zapier / Make): a weekly schedule → HTTP request to the actor API with your watch list → append the dataset to a sheet or warehouse table keyed on instahyreEmployerId + run date → alert when newJobsLast7Days jumps.

📊 Pricing

Pay-per-event: company-signal per delivered company row and job-record per delivered job row. SUMMARY rows (empty results, rejected input) are never billed. View current pricing.

You pay for the rows you receive, so maxResults is also your spending cap. For scale: the prefilled example input scanned 656 open roles with 43 requests and returned 200 company rows (run-a3-prefill).

❓ FAQ

Do I need an Instahyre account, login or API key? No. The actor reads the same public job search the website uses, plus the public job sitemap for posting dates.

How current is the data? Every run queries Instahyre live. Open-role counts are as of the run; posting dates come from Instahyre's job sitemap, and roles newer than the latest sitemap are dated to the run day — correct for both such roles in our date check, but it can be a day late for a role posted on the sitemap's own last day.

How accurate are the posting dates? On 2026-09-10, 10 of 10 jobs checked against their job page's own datePosted were exact (13 Aug – 10 Sep, run run-b-jobs-python), and 11 of 12 in a second sample that included postings edited after publication; the one miss was a day late. Roles posted after Instahyre last rebuilt its sitemap are dated to the run day.

Why are earliestPostedAt / lastPostedAt or postedAt sometimes empty? Dates are resolved only for roles posted since the date horizon — your window plus two weeks (about six weeks with the default window). Older roles that are still open are counted in activeJobs and undatedJobs, never in the new-role counts. With the prefilled example input, 481 of the 633 open roles behind the 200 rows (76.0%) predated the horizon (2026-07-24), so 119 of the 200 companies have no dated role (run-a3-prefill).

Does newJobsInWindow count roles that were opened and already closed? No. Instahyre's search returns the roles listed at run time and drops closed ones (its total fell from 13,610 to 13,387 within eight minutes while we measured), so velocity means new roles that are still listed at run time.

Why no recruiter names or contacts? By design. Instahyre's job records name the recruiter who posted a role; that is personal data (India's DPDP Act, GDPR), so the actor drops those fields the moment a record arrives and never stores them. Company-level data is what a hiring signal needs.

How long does a run take? Measured locally without a proxy on 2026-09-10: the prefilled example input (656 roles, 43 requests) took 117 s, of which 50 s were three rate-limit pauses (5, 15 and 30 s), after which the run slowed itself by 2 s per request (run-a3-prefill); 100 jobs-mode rows took 14 s (run-b-jobs-python); a three-name watch list took 12 s (run-c-watchlist). A scan costs one request per 35 matching roles in each function it reads, plus about 9 fixed requests (7 for posting dates, a probe and an internship check) and any rate-limit retries. On Apify, with the default proxy, these timings have not been measured yet.

How many new roles appear per day? Instahyre-wide, 71–186 new roles per weekday (median 139) and 7–27 per weekend day between 26 Aug and 8 Sep 2026, counted from Instahyre's job sitemap with the same dating method. A 7-day window always contains a weekend, so compare weeks with weeks.

Can I export to CSV / Excel / JSON? Yes — directly from the Apify dataset. For CSV, topFunctions and topSkills are lists of {function, count} and {skill, count} objects; flatten them in your tool of choice.

🐛 Troubleshooting

• "Instahyre rejected the query — locations: Invalid location." — the city is not spelled the way Instahyre spells it; use one of the names in the input description. The run stops without charging.
• A watch-list company has no row — the log and the SUMMARY record say why: either the name is not an Instahyre employer name (check the spelling on the company's Instahyre page) or it has no open role matching your other filters.
• One SUMMARY row and nothing else — your filters are valid but match no open role right now; the row's hint suggests which filter to relax.
• "HTTP 429 — pausing all requests" in the log — Instahyre's rate limit; the actor waits and continues on its own. Keep maxConcurrency at 2 or lower.
• Velocity counts are empty (null) — the job sitemap could not be read in that run (for example a Cloudflare check on the proxy IP); the log says so. Open-role counts are still correct; run it again later.

⚠️ Trademark

Independent, third-party tool. Not affiliated with, endorsed by or connected to Instahyre or Blob Infotech Private Limited. "Instahyre" and related marks belong to their owners and are used here for identification only.

⚖️ Is it legal to scrape this data?

This actor reads publicly listed job postings and employer profiles from Instahyre without logging in, at a polite rate, and deliberately collects no personal data — recruiter names, designations and profile photos are discarded. Instahyre's Terms of Use govern how its content may be used; review them for your use case. Job descriptions (optional) are published text and could still mention a person; personal data is protected by India's DPDP Act, the GDPR and similar laws, so only process it with a legitimate basis. See Apify's blog post on the legality of web scraping.

🤝 Support & contact

• 🌐 Website: data.foxlabs.com.tr
• 📧 Email: info@foxlabs.com.tr
• 🐛 Issues: open a ticket in the Actor's Issues tab
• 🧰 More clean B2B data actors: Fox Labs on Apify

Changelog

0.1 — 2026-09-10 — initial release

• agencyFlag / agencySignals removed before release. Instahyre lists an agency-posted role under the client company, so a self-description heuristic flagged none of 244 employers in testing, and a column that is always false would mislead.
• foundedYear returns null for Instahyre's 1900 placeholder (5 of 297 employers in testing).
• Two outputs from Instahyre's public job search: companies (one row per employer with hiring velocity — open roles, new roles in the last 7 days and in a 1–8 week window, function and skill mix, sample titles, headcount bucket, founded year, tagline, Instahyre page) and jobs (one PII-free row per listing, optional plain-text description and required experience).
• Filters mapped to Instahyre's own facets: locations, 19 categories / 107 job functions, skills, a company watch list, company size, 74 industries, experience years.
• Posting dates from Instahyre's job sitemap (earliest lastmod at or above each job ID). Checked on 2026-09-10 against job pages' own datePosted: 10 of 10 exact, and 11 of 12 in a second sample (the miss was a day late). If the sitemap cannot be read, velocity counts and postedAt are null, never a misleading 0.
• Watch lists: a name Instahyre does not know is reported and skipped; the rest of the list still runs. Companies with no matching open role are named in the log and the SUMMARY record.
• A valid filter that matches nothing succeeds with one explanatory SUMMARY row; a rejected value (e.g. an unknown city) fails with the same explanation. SUMMARY rows are never billed.
• Rate limits: an HTTP 429 pauses every worker (5, 15, 30, then 60 s) and slows the rest of the run; network resets are retried on their own counter.
• Large result sets: every part of a scan stays inside Instahyre's 10,000-result window; a part that cannot be split further is read up to the window and flagged in the log instead of failing the run. A pick that mixes whole categories with single functions is checked with one combined function query, so it cannot come back falsely empty.
• Privacy: recruiter name, designation and profile fields never reach the dataset — the default path never requests them, and detail records (includeDescriptions) are reduced on arrival to description, experience, category, functions and the internship/active flags.