We extract entry-level job listings, walk-in schedules, eligibility criteria, and company profiles from Freshersworld. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Job Postings objects from freshersworld.com. All fields typed and schema-versioned.
"job_id": "FW-982341", "title": "Software Development Engineer", "company_name": "Tech Mahindra", "location": "Pune", "experience_required": "0-1 Years", "salary_range": "3.5 - 4.5 LPA", "posted_date": "2026-05-10"
| # | job_id | title | company_name | location | role_category | experience_required |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Walk-In Details objects from freshersworld.com. All fields typed and schema-versioned.
"job_id": "FW-W-4412", "company_name": "TCS", "city": "Bengaluru", "start_date": "2026-05-15T09:00:00Z", "end_date": "2026-05-16T17:00:00Z", "documents_required": "['Resume', 'Govt ID', 'Degree Certificate']", "eligibility_summary": "B.E/B.Tech 2025 batch only"
| # | job_id | company_name | venue_address | city | start_date | end_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Eligibility Criteria objects from freshersworld.com. All fields typed and schema-versioned.
"job_id": "FW-982341", "degree_required": "['B.E', 'B.Tech', 'MCA']", "branches_allowed": "['CS', 'IT', 'ECE']", "minimum_percentage": 60.0, "passout_year": "[2025, 2026]", "backlogs_allowed": false, "age_limit": 25
| # | job_id | degree_required | branches_allowed | minimum_percentage | passout_year | backlogs_allowed |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Company Profiles objects from freshersworld.com. All fields typed and schema-versioned.
"company_id": "CMP-1029", "name": "Infosys", "industry": "IT Services", "hq_location": "Bengaluru", "employee_count": "300,000+", "total_jobs_posted": 412, "website": "infosys.com"
| # | company_id | name | industry | website | about_text | employee_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Government Jobs objects from freshersworld.com. All fields typed and schema-versioned.
"notification_id": "GOV-SSC-2026", "department_name": "Staff Selection Commission", "post_name": "Junior Engineer", "total_vacancies": 842, "qualification": "Diploma/Degree in Engineering", "last_date_to_apply": "2026-06-15", "official_notification_url": "ssc.nic.in/notice.pdf"
| # | notification_id | department_name | post_name | total_vacancies | qualification | age_limit |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Freshersworld pipeline navigates ad-heavy layouts, extracts structured eligibility criteria, and normalises relative dates into clean timestamps.
Capture title, location, salary ranges, and required skills for thousands of fresher listings daily.
Extract venue addresses, dates, and contact details for offline recruitment drives across tier-1 and tier-2 cities.
Monitor state and central government notifications, vacancy counts, and official PDF links.
Convert unstructured text into structured arrays for degree, branch, passout year, and minimum percentage requirements.
Standardise skill requirements from free-text descriptions into clean, queryable arrays.
Parse LPA and monthly stipend figures, normalising irregular formatting into absolute numeric ranges.
Extract employer details, industry classification, and historical job posting volume.
Bypass heavy ad placements and promotional modals to extract strictly the core job data.
Run pipelines daily or weekly to capture new postings and detect expired listings automatically.
Brief in. Clean data out.
Provide target categories, locations, or job roles. We design the extraction schema together.
We configure Scrapy crawlers, ad-blocking middleware, and proxy rotation for freshersworld.com.
Schema validation, date normalisation checks, and field completeness tests before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage.
Extracting clean data from job boards requires handling messy text and ad-heavy DOMs. Here is how we ensure data quality.
Freshersworld relies heavily on display ads and popups which disrupt standard DOM traversal. Our crawlers utilise ad-blocking middleware to strip non-essential nodes, ensuring selectors target only the job listing content.
Job boards frequently use relative dates like 'Posted 2 days ago'. Our pipeline calculates the absolute timestamp based on the crawl execution time, delivering ISO 8601 formatted dates for accurate time-series analysis.
Employers post eligibility criteria in free-text paragraphs. We apply regex and NLP pipelines to extract specific degrees, passout years, and percentage cut-offs into structured JSON arrays.
Volumetric scraping triggers IP bans. We distribute requests across Indian residential IP pools, maintaining optimal concurrency limits to extract data reliably without triggering rate limits.
We maintain state for all active job IDs. When a listing is removed or marked expired on Freshersworld, our pipeline emits a status update, ensuring your downstream database reflects the live market.
Job boards and career portals ingest entry-level listings to backfill their own search indexes.
Analysts track hiring volumes, salary trends, and skill demand across tier-1 and tier-2 Indian cities.
Colleges monitor walk-in drives and entry-level hiring patterns to guide student placement strategies.
HR teams track competitor job postings to benchmark fresher salaries and recruitment volume.
EdTech platforms identify companies hiring for specific tech stacks to tailor their B2B placement pitches.
Economists aggregate entry-level job data to measure graduate employment health and sector growth.
"Freshersworld holds the pulse of India's entry-level job market, but extracting structured data from its ad-heavy DOM requires resilient infrastructure."
Most teams underestimate the investment required. Reliable Freshersworld scraping requires residential proxies, strict date normalisation, and ad-blocker integration to parse clean text. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our freshersworld.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic, optimised for high-throughput text extraction.
Post-processing scripts clean salary strings, map relative dates to absolute timestamps, and extract structured arrays from raw HTML text.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About freshersworld.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available job listings is generally permissible. DataFlirt targets only public, non-authenticated job and walk-in data. We do not bypass recruiter logins or extract proprietary premium content.
Our change detection system monitors previously scraped job URLs. If a listing returns a 404 or an 'expired' tag in the DOM, we emit an update record to flag the job as closed in your database.
Yes. We parse the free-text descriptions to extract required degrees, passout years, and minimum percentage criteria into structured JSON fields.
Pipelines typically run daily to capture new job postings. For specific categories like walk-ins, we can configure sub-daily runs to ensure high freshness.
Yes, we track the government and defense sections, extracting vacancy counts, application deadlines, and links to the official PDF notifications.
We price based on volume and delivery frequency. Contact us with your target categories and data volume for a scoped quote.
Yes. We provide a sample run of up to 500 job listings during the scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need daily fresher job updates or historical walk-in data, we scope, build, and operate the pipeline. Tell us what you need.
