ConfiguredData Collection

Job Market Data Feed

Turn approved job searches and public listings into a normalized feed of roles, employers, locations, salary signals, requirements, benefits, and application routes.

No access or payment before scope confirmation

Your input

Tell us what to run. We handle the operating structure.

You do not need to prepare technical configuration. Provide the business requirements, examples, and approved access; we translate them into fields, rules, and a tested schedule.

What you provide

Approved roles, keywords, employers, industries, and locations
Radius, date, remote, employment-type, salary, and application-route filters
Required job, employer, description, salary, and location fields
Role-family, seniority, location, pay-period, and currency normalization rules
Duplicate, stale, closed, sponsored, and external-apply handling
Frequency, record limits, retention, delivery destination, and named reviewers

How you provide it

Setup form
Spreadsheet of approved searches or job URLs
Workforce or labor-market research brief
Role and location taxonomy
Example job-market table or API schema
Written employment-use, privacy, normalization, retention, and review rules

The result

What this workflow delivers.

A source-linked labor-market dataset that teams and AI agents can retrieve, compare, summarize, and route into approved research, workforce-planning, or recruiting workflows.

Best for: People analytics, workforce strategy, recruiting operations, compensation research, economic research, location strategy, education planning, and market-intelligence teams.

Sources

Approved public job-search result pages
Approved job-posting URLs
Customer-supplied role, employer, location, radius, date, workplace-type, and employment-type filters
Public employer websites when an external application route is included
Public role-based employer contact pages only when separately approved
Approved public Middle East and North Africa job-search and detail pages

Output fields

Job title, employer, source URL, listing identifier, first-observed date, and source-posted age
Raw and normalized city, region, country, coordinates, workplace type, and employment type
Raw salary text, currency, pay period, displayed range, salary-source label, and normalized annual range when approved
Job description, requirements, benefits, industry, category, employer summary, and company website when available
Direct or external application route and closed, duplicate, stale, missing, or unavailable state
Collection query, filters, timestamp, deduplication key, confidence state, and human-review status
Career level, experience, skills, vacancies, job function, company size, and benefits when displayed

Delivery options

CSV download
JSON download
Airtable base or table
Google Sheets
Excel
Database or warehouse-ready table
Scoped API endpoint
Webhook-ready change feed

Operating scope

Quoted by searches, locations, result depth, job pages, fields, frequency, history, and review requirements
One-time, daily, weekly, or monthly
Public sources

AI-ready delivery

Structured data your team and agents can rely on.

Receive normalized records directly or let an approved agent retrieve them through a scoped interface. Source evidence, transformations, timestamps, and exception states remain available for review.

Use it directly

CSV and JSON exports
Airtable or spreadsheet delivery
Database and warehouse-ready records
Customer-controlled backups

Connect approved agents

Scoped API or webhook access
Filter and retrieve defined records
Summarize, compare, classify, and cite
Route exceptions to a human owner

Keep control

Customer-owned resulting dataset
Raw and normalized values remain distinct
Model, API, hosting, and storage costs are scoped
No autonomous consequential authority

Configurable service

One workflow, configured around the decisions your team owns.

The modules describe business capabilities, not separate tools to operate. Select the coverage, filters, review rules, schedule, and destination during setup.

Available modules

Search and location collection - run approved role and geography searches
Job detail enrichment - retain descriptions, requirements, benefits, salary, employer, and application routes
Normalization - separate raw roles, locations, pay periods, and salary values from calculated fields
Change history - append newly observed, changed, closed, stale, and unavailable states
AI-ready retrieval - expose source-linked structured records through approved files, tables, or API routes
Exception review - route duplicates, ambiguous salaries, missing fields, and unavailable pages for human review

Business questions supported

Which roles and skills are newly visible in each market?
How is source-visible hiring demand changing by employer, role family, location, and workplace type?
Which salary signals are employer displayed versus estimated or calculated?
Which listings are duplicated, stale, closed, unavailable, or missing required fields?
What source URL and collection time support each job record?
Which records can an approved AI agent retrieve or summarize, and which require human review?

Worked example

See what goes in and what comes back.

Examples show the delivery structure before setup. Names and values are illustrative, not client records or performance claims.

Example input

{
  "searches": [
    {
      "role": "Data Analyst",
      "location": "Chicago, IL",
      "radius_miles": 25
    },
    {
      "role": "Backend Engineer",
      "location": "Dublin, Ireland",
      "remote": true
    }
  ],
  "max_results_per_search": 200,
  "date_window_days": 14,
  "required_fields": [
    "title",
    "employer",
    "location",
    "salary",
    "description",
    "application_url"
  ],
  "normalize_roles": true,
  "frequency": "Weekly",
  "delivery": [
    "Airtable",
    "Scoped API"
  ]
}

Example delivery

Illustrative record

{
  "job_title_raw": "Senior Data Analyst",
  "role_family_normalized": "Data Analytics",
  "employer": "Example Research Group",
  "location_raw": "Chicago, IL",
  "workplace_type_normalized": "Hybrid",
  "salary_raw": "$95,000-$120,000 yearly",
  "salary_min_annual_calculated": 95000,
  "salary_max_annual_calculated": 120000,
  "salary_source": "Employer displayed",
  "source_url": "https://www.example-job-board.test/jobs/synthetic-101",
  "first_observed_at": "2026-08-19T09:00:00Z",
  "record_state": "complete",
  "example_status": "synthetic"
}

Installation path

From source approval to scheduled operation.

The first representative run is reviewed before the workflow becomes a recurring operation.

Confirm approved roles, employers, locations, filters, fields, intended decisions, and prohibited employment uses

Run a representative sample and inspect duplicates, salary labels, location quality, application routes, descriptions, and missing states

Agree role, location, salary, employer, and workplace normalization rules plus retention and delivery

Collect approved public listings within documented source and request boundaries

Append timestamped observations and preserve raw fields separately from normalization and AI-assisted extraction

Deliver complete, duplicate, closed, stale, unavailable, partial, and review-required records separately

Managed history

Each run adds to a useful operating history.

Recurring runs append timestamped job observations so newly observed, changed, duplicated, closed, stale, or unavailable listings can be compared without overwriting prior states.

Retention and portability

The resulting dataset belongs to the customer. Delivery can be made as CSV, JSON, Airtable, spreadsheets, a database, warehouse, webhook, or scoped API. Aineed Data retains only the managed copy and history agreed for operation. Customer-controlled backups, snapshot frequency, portability, deletion, and exit exports are defined during setup.

What the accumulated history can support

Retrieve matching roles for an AI research or workforce-planning agent
Summarize hiring demand by role, employer, location, industry, and workplace type
Compare source-displayed salary ranges with explicit sample and normalization boundaries
Detect newly observed, changed, stale, duplicated, or closed postings
Extract skills and requirements into an approved role taxonomy
Route review-required listings to a human owner
Ground generated briefs in source URLs, raw fields, and collection timestamps
Supply structured records to approved matching or forecasting models without making employment decisions
Compare source-visible role, skill, salary, and career-level demand across approved Middle East and North Africa markets

Interpretation limits

History makes comparison possible, but it does not remove source limitations or turn signals into guaranteed business outcomes.

Job listings can be sponsored, duplicated, stale, estimated, removed, syndicated, or linked through third parties

Posting age, salary, benefits, remote status, location, application routes, and employer details can be missing or source-controlled

A visible listing does not prove active hiring, budget, headcount growth, employer identity, or application availability

Salary comparisons depend on pay period, currency, location, experience, commission, benefits, and source methodology

AI-assisted skill extraction and role normalization can omit context or misclassify requirements

Coverage varies by query, location, date window, source ranking, and collection time

Pages can be blocked, unavailable, rate-limited, or changed after collection

Preferred-candidate fields can reflect discriminatory or unlawful criteria and are excluded from automated decision use

Safeguards

Automation stays inside agreed boundaries.

Access, retention, exports, and operating controls are confirmed for this workflow before launch.

Public job and employer sources only; no candidate accounts, resumes, credentials, or private applicant data

No passwords, cookies, tokens, MFA codes, private keys, or session exports requested

No bypassing access controls, publisher restrictions, geographic controls, licensing, or request limits

Personal employer contacts and inferred email patterns are excluded; role-based contacts require separate approval

No automated applications, candidate ranking, hiring, compensation, employment, or immigration decisions

Salary estimates remain labeled by source, pay period, location, and displayed versus calculated status

No claim that a posting is active, genuine, complete, employer-authored, or still accepting applications

No job-board affiliation, endorsement, official API access, exhaustive coverage, or guaranteed freshness

Preferred gender, nationality, and residence fields are excluded from AI matching, candidate ranking, and employment decisions

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Start setup

Configure Job Market Data Feed.

Share the sources, rules, and destination. We’ll verify access and confirm the final setup and monthly operating scope.

Setup$700

ManagedQuoted by search and record volume

Normally liveConfirmed after sample

Job Market Data Feed

Tell us what to run. We handle the operating structure.

What you provide

How you provide it

What this workflow delivers.

Sources

Output fields

Delivery options

Operating scope

Structured data your team and agents can rely on.

Use it directly

Connect approved agents

Keep control

One workflow, configured around the decisions your team owns.

Available modules

Business questions supported

See what goes in and what comes back.

From source approval to scheduled operation.

Each run adds to a useful operating history.

What the accumulated history can support

Automation stays inside agreed boundaries.

Continue through the catalogue.

Competitive Price & Assortment Intelligence

Supplier Quote Normalizer

Portal Report Collector

Configure Job Market Data Feed.

Configure the workflow.