Time series · from our own crawl

Hiring momentum

Most job-market charts count postings. This one counts changes — roles appearing on company career pages, and roles disappearing from them. It is the difference between knowing how many jobs exist and knowing which way the number is moving.

Roles opened

1,291

17 Jul – 23 Jul

Status: Healthy

Roles closed

1,119

filled, cancelled or reposted

Net change

+172

openings minus closures

Status: Healthy

Opened per closed

1.15

above 1.00 means expanding

Status: Healthy

Openings and closures by day

Each point is one crawl observation. Where the opening line sits above the closing line, the market added roles that day.

  • Roles opened
  • Roles closed
Roles opened versus roles closed per observation day from 2026-07-17 to 2026-07-23
Roles opened versus roles closed per observation day from 2026-07-17 to 2026-07-23
Point Roles openedRoles closed
17 Jul 14089
22 Jul 1,029912
23 Jul 122118

Net adding roles

Employers who opened more than they closed, among those with at least 5 recorded events.

  1. OpenAI+22
  2. Nagarro+4
  3. Stripe+1
  4. Toast+7
  5. MongoDB+8
  6. Airbnb+1
  7. Okta+2
  8. Databricks+10
  9. Agoda+22
  10. Fivetran+60

Net removing roles

Closures outpaced openings here. Usually this means roles were filled — it is not a layoff signal.

  1. Continental−21
  2. Paytm−10
  3. Zenoti−10
  4. Roku−9
  5. Workato−9
  6. Jfrog−9
  7. Roblox−7
  8. Tide−6
  9. Salesforce−5
  10. Commvault−5

How this is measured

Every crawl records when a listing was first seen and, once it stops appearing on the employer's careers page, when it closed. Counting those transitions gives real events rather than an estimate derived from posting dates.

What it does not tell you: whether a closed role was filled, cancelled or simply reposted under a new listing ID. From outside the company those look identical, so treat closures as churn rather than as outcomes.

Excluded: 2026-07-15, 2026-07-16, 2026-07-24, 2026-07-25 — first-crawl backfill of 24,212 listings, which is catalogue ingestion rather than hiring.

Captured 25 Jul 2026 · 25,503 listings tracked · 7 observation days, 3 usable

Questions

Are companies opening more jobs than they are closing?

Across 3 observation days between 2026-07-17 and 2026-07-23, we recorded 1,291 roles opening and 1,119 closing — a net of +172. That works out to 1.15 roles opened for every role closed. This is a short window and should be read as a current reading, not a trend.

How does OnJob measure hiring momentum?

Every crawl stamps each listing with when we first saw it and, once it disappears from the employer's careers page, when it closed. Counting those transitions gives real openings and closures rather than an estimate. It measures listing lifecycle, not headcount: a role can close because it was filled, cancelled, or reposted under a new ID, and we cannot tell those apart from the outside.

Why is one of the days excluded from the chart?

Because it is a backfill, not hiring. The first crawl inserts the entire catalogue at once — on 2026-07-15 and 2026-07-16 and 2026-07-24 and 2026-07-25 that was 24,212 listings appearing on a single day. Plotted as-is it would read as an enormous hiring surge followed by a collapse. The capture script flags any day whose intake is more than three times the median of the others, and those days are excluded from every figure on this page.

Is this the same as a layoff tracker?

No, and it should not be read as one. A closed listing usually means the role was filled, which is the opposite of a layoff. We publish this instead of a layoff tracker because there is no free, reliable, structured source of Indian layoff data, and a hand-maintained list would go stale without anyone noticing. Listing lifecycle is something we can actually measure and keep current.

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