Q
QuickCommerceJobs

How we built this platform.

Every data source, verification step, and calculation formula - explained. No black boxes.

Version 1.0
01

Our mission

We built QuickCommerceJobs to solve a specific problem: there is no dedicated job platform for India's 80,000+ dark store workers. Hiring in quick commerce today is fragmented across WhatsApp groups, pamphlets, staffing agencies, and word of mouth.

A worker searching “Blinkit dark store job near me” finds nothing useful. We want to change that.

This page explains how we turn raw data into useful, trustworthy job information. We believe transparency builds trust, and trust is the foundation of any job platform.

02

Where the data comes from

Dark store locations

We maintain a database of 4,081 dark stores across India, sourced from three platforms:

Blinkit (1,954 stores)
Store coordinates obtained via trilateration from Blinkit's
public-facing API. Accurate to within 0–50 meters for most stores.
Last scraped: March 15–17, 2026.

Zepto (1,089 stores)
Store names, coordinates, city, and state obtained from Zepto's
public serviceability API.
Last scraped: March 14–15, 2026.

Swiggy Instamart (1,038 stores)
Store coordinates and locality names obtained from Swiggy's
public API.
Last scraped: March 18–19, 2026.

All data was collected using publicly-available endpoints. We do not access private or authenticated APIs. We do not collect user data from these platforms.

Job listings

We generate job listings by combining the dark store data above with:

  • Standardized role definitions (picker/packer, shift incharge, store manager, etc.) based on publicly-known dark store operations
  • Platform-specific role titles sourced from public job postings on Naukri, Indeed, WorkIndia, JobHai, Glassdoor, and LinkedIn
  • Job descriptions written based on real job postings from these same public sources

Salary data

Salary ranges are compiled from multiple public sources:

  • Glassdoor salary reports
  • Indeed company salary pages
  • Naukri job postings with salary disclosed
  • WorkIndia and JobHai listings
  • AmbitionBox employee-submitted data
  • Public interviews and reports from industry sources

We cross-reference these sources and normalize salary data by standardized role category, platform (Blinkit, Zepto, Swiggy Instamart), and city tier (Tier 1 Metro, Tier 1 Non-Metro, Tier 2).

03

How often we update

  • Dark store locations: Quarterly (every 3 months) - dark store networks change slowly, so monthly re-scraping isn't necessary
  • Job listings: Daily - new listings are generated based on our data, old listings expire after 30 days
  • Salary ranges: Quarterly - compiled from fresh data pulls from our sources
  • City and area summaries: Updated automatically whenever underlying data changes

You can see the timestamp of when any city page or listing was last updated at the top of that page.

04

How we verify listings

Our verification levels:

Verified ✓
We have manually confirmed this listing by contacting the dark
store manager or a staffing agency handling hiring for this store.
These listings show a green "Verified" badge.

Auto-generated
The listing is based on our dark store database. We know a dark
store exists at this location and we know this platform typically
hires for this role. We have not manually confirmed whether this
specific store is currently hiring.

We are transparent: most of our launch-day listings are auto-generated, not manually verified. We'll expand verification as our network of recruiter partnerships grows.

We never pretend auto-generated listings are verified.

05

How we calculate salaries

Base salary ranges

For each role × platform × city tier combination, we compile salary data from our sources and compute:

  • min - the 10th percentile of reported salaries
  • max - the 90th percentile of reported salaries
  • avg - the median of reported salaries

Take-home salary formula

Gross Salary = Base Salary + Overtime + Night Allowance + Attendance Bonus

Where:
  Base Salary   = midpoint of the range for that role / platform / city
  Overtime      = (OT hours) × (hourly rate)
  Hourly rate   = Base Salary ÷ (30 days × 8 hours) = Base Salary ÷ 240
  Night Allow.  = (night shifts) × ₹60 (typical rate)
  Attend. Bonus = ₹1,500 (if full attendance selected)

Deductions:
  PF  (Provident Fund)            = 12% of basic salary
  ESI (Employee State Insurance)  = 0.75% of gross salary

Net Take-Home = Gross Salary − PF − ESI

Salary ranges by role level

LevelTier 1 MetroTier 1 Non-MetroTier 2
Entry (Picker/Packer)₹14k–22k₹12k–18k₹11k–16k
Mid (Shift Incharge)₹20k–30k₹18k–26k₹16k–22k
Senior (Store Manager)₹35k–70k₹30k–55k₹25k–45k
Delivery (Gig)₹18k–35k₹15k–28k₹12k–22k

Disclaimers

  • These are estimates based on industry norms, not guarantees
  • Actual deductions may vary based on the specific employment contract
  • Some staffing agencies apply different deduction structures
  • Overtime rates may vary by platform and city
06

Our role classification system

Different platforms call the same job by different names. We maintain a standardized role taxonomy to compare across platforms:

Standard RoleBlinkitZeptoSwiggy
Picker / PackerCaptainPicker / PackerPicker Executive
LoaderPicker / LoaderLoaderPicker & Loader
Scanning & BillingScanning AssociateBilling AssociateStore Associate
Shift InchargeStore InchargeShift InchargeAsst. Store Incharge
Store ManagerStore ManagerDark Store ManagerStore Manager
Delivery PartnerDelivery PartnerRiderDelivery Executive
Warehouse HelperHelperStore HelperWarehouse Associate
Quality CheckerQC AssociateQC AssociateQC Associate
Area ManagerArea ManagerArea ManagerArea Manager

When you see a role like “Picker/Packer” on our platform, we map it to whichever platform-specific title applies for the listing you're viewing.

07

Area and city groupings

Dark stores are grouped by area (locality) within cities. For example, “Mansarovar, Jaipur” is an area containing 5 dark stores across Blinkit, Zepto, and Swiggy.

Locality names come from reverse geocoding store coordinates using a three-step fallback chain:

1. Ola Maps API (primary - best Indian locality data)
2. Mappls API (fallback)
3. OpenStreetMap Nominatim (final fallback)

We normalize locality names to handle variations (“MANSAROVAR”, “Mansarovar”, “Man Sarovar” all map to “Mansarovar”).

City name normalization

  • Bengaluru → Bangalore
  • Gurugram → Gurgaon
  • Kolkata / Calcutta → Kolkata
  • Mumbai / Bombay → Mumbai

City tier classification

  • Tier 1 Metro: Delhi NCR, Mumbai, Bangalore, Hyderabad, Chennai, Kolkata, Pune (~20% higher base salaries)
  • Tier 1 Non-Metro: Jaipur, Lucknow, Ahmedabad, Chandigarh, Kochi, Indore (moderate salaries)
  • Tier 2: All other cities (lower base, lower cost of living)
08

Handling errors and edge cases

Our data is not perfect. Here's how we handle common issues:

A dark store has closed

If a store in our database has closed, we'll remove it within 30 days of being notified. Use the “Report this listing” link on any listing page to report closures.

Wrong salary data

Salary ranges are based on aggregate data from public sources. If you believe our range is incorrect for a specific role/city/platform, email [email protected] with your source.

Wrong location data

If a store is geocoded incorrectly (shown in the wrong area), report it via the same email. We manually verify and update.

A new store has opened

Our scraping runs quarterly. If a new store opened recently and isn't on our map, it will appear in the next refresh cycle.

Missing cities

We only include cities where at least one of Blinkit, Zepto, or Swiggy Instamart operates. If your city isn't here, it's because none of these platforms have launched there yet.

09

What we don't know

We believe honest limitations are better than false precision. Here is what we don't know:

  • Exact current headcount of each dark store (we estimate 10–20 workers per store based on industry reports)
  • Which specific stores are actively hiring today (unless verified)
  • Internal salary bands at platform-specific senior levels
  • Exact benefits offered at specific stores (we list general platform-wide benefits)
  • Performance-based bonuses or incentives beyond what platforms publicly disclose
  • Exact shift availability at specific stores
  • Manager or HR contact info for specific stores (we're building this)
10

Editorial independence

QuickCommerceJobs.com is published by Apexlayer Technologies Private Limited, an independent company with no investment, ownership, or commercial relationship with Blinkit, Zepto, Swiggy Instamart, or their parent organizations. We are a DPIIT-recognized startup operating under Indian law. Specifically, we are not:

  • Owned by, invested in, or in partnership with Blinkit, Zepto, Swiggy Instamart, or any parent company (Zomato, Kiranakart Technologies, Swiggy)
  • Paid by these platforms to promote their listings
  • Under any editorial control or influence from any staffing agency or recruiter

Our content decisions are made by:

  • Sachin Gurjar (Founder) - overall strategy and editorial standards
  • Our data pipeline - automated listing generation from verified sources

If you believe any content on our platform is biased, unfair, or compromised by commercial interests, email [email protected] directly.

11

Changelog

Version 1.0

April 2026

  • Launched QuickCommerceJobs platform
  • Initial data scrape of 4,081 dark stores
  • Salary ranges based on Q1 2026 data
  • 5 core role categories supported
  • Coverage across Blinkit, Zepto, and Swiggy Instamart