The 8 Best Job APIs to Use in 2026 – Full Comparison

In this article, we are going to cover:

• What job API, datasets, and DIY scraping are, and how to choose the right approach for your use case
• The best job data APIs and providers in 2026, with a full breakdown of features, sources, pricing, and limitations
• How to match the right provider to your specific use case, whether you’re building a job board, training an AI model, or running labor market research

💡 Bright Data also provides ready-to-use datasets and managed data services

TLDR: All Providers at a Glance

Whether you are building a job board, powering a sales intelligence tool, or running labor market research, the method you use to collect job data will define your project’s ceiling. Build a scraper from scratch and you inherit every maintenance headache that comes with it: broken parsers when sites restructure, CAPTCHA arms races, deduplication logic you wrote yourself at 2 AM. Use the right API or dataset provider and those problems disappear.

This guide cuts through the noise. Below you will find the top job APIs and data providers in 2026, what they actually deliver, what they cost, where they fall short, and which use case each one fits best.

API vs Dataset vs Scraper: Choose Your Approach First

Before you evaluate providers, you need to be clear on what kind of product you are buying. The three options work very differently.

Job APIs let you query a provider’s database in real time via REST endpoints. You send a request, get structured JSON back. Best for: job boards that need live search, sales tools triggering on fresh postings, and applications where latency matters.

Pre-built datasets are bulk exports of tens or hundreds of millions of records delivered to your cloud storage (S3, GCS, Azure, Snowflake). You download once or subscribe to periodic refreshes. Best for: AI/ML training, bulk historical analysis, and workflows where you process data offline. Cost per record is significantly lower than API calls at scale.

DIY scraping means you build and maintain everything yourself. Tools like Bright Data’s proxies can handle the infrastructure layer, but the parsing logic, deduplication, and schema normalization are still on you. Best for: niche sources no provider covers yet, or when you need maximum control. Ongoing maintenance typically costs 20+ hours per month per scraper target. For a deeper look at what that entails, see the common challenges of building your own web scrapers.

A practical rule of thumb: if you need fewer than 50K records per month and real-time access, an API is usually cheaper and simpler. Above that volume, datasets become more cost-effective. If your target sources do not exist in any provider’s catalog, build with infrastructure tools.

The Best Job APIs and Data Providers in 2026

1. Bright Data: Best Overall for Enterprise-Grade Flexibility

Bright Data does not offer a single job product. It offers an ecosystem. You can buy pre-built datasets, scrape in real time via dedicated Scraper APIs, build custom pipelines using Scraper Studio (a no-code scraper), or pull from the Web Archive for historical snapshots. This flexibility is what separates it from every other provider on this list.

Datasets and scrapers available:

• LinkedIn Scraper API
• Glassdoor Scraper API
• Indeed Scraper API
• LinkedIn job listings: 57M+ records
• Indeed job listings: 46M+ records
• Glassdoor listings: 36M+ records

And a lot more.

Each dataset ships in JSON, CSV, NDJSON, JSON Lines, or Parquet, and can be delivered directly to S3, Snowflake, Google Cloud, Azure, or SFTP. You can subscribe for monthly, quarterly, or biannual refreshes, or purchase a one-time snapshot. The AI filter feature lets you describe your data requirements in plain English and have filters applied automatically, a genuine time saver when you are narrowing 86M records down to what you actually need.

For real-time access, the LinkedIn Jobs Scraper API starts at $1.50/1K records on pay-as-you-go, or $0.75 to $0.98/1K records on monthly subscription plans. Dedicated scrapers exist for Indeed and Glassdoor jobs as well.

What sets Bright Data apart:

• Full GDPR and CCPA compliance with ISO 27001 certification, so the legal risk shifts to Bright Data and not your team
• 70+ integrations including Zapier, n8n, Make, LangChain, LlamaIndex, and CrewAI
• AI-optimized datasets with code examples for ChatGPT and Claude integration out of the box
• Official MCP server for AI agent frameworks
• Free sample datasets in JSON/CSV before you commit to a purchase
• 24/7 support from 80+ data professionals, with dedicated account managers at scale

Pricing: Datasets start at $2.50/1K records ($250 minimum order). Scraper APIs start at $0.75/1K records on subscription. 7-day free trial available.

Best for: Enterprises, AI/ML teams, and researchers who need multi-source coverage with no infrastructure overhead and full compliance built in.

Not the right fit if: You need fewer than 5K records and want a free tier. TheirStack or SerpApi serve that scenario better.

2. Coresignal: Best for LinkedIn-Heavy Workflows with Employee Context

Coresignal’s main selling point is the depth of LinkedIn data combined with employee and company enrichment in a single platform. Its multi-source jobs dataset includes 399M+ job posting records from LinkedIn, Indeed, Glassdoor, and Wellfound, deduplicated and enriched with 65+ data points per job, including recruiter information, seniority flags, and company firmographics. For teams evaluating alternatives, a comparison of top Coresignal alternatives can help benchmark where it fits relative to other providers.

The API works on a credit system: 1 Collect credit equals 1 record. The multi-source jobs product costs 2 credits per record because of the enrichment, which doubles the cost but saves you from building deduplication and company-join pipelines yourself.

Pricing tiers (API):

• Starter: from $49/month (250 Collect / 500 Search credits)
• Pro: from $800/month (10,000 Collect / 20,000 Search credits)
• Premium: from $1,500/month (50,000 Collect / 150,000 Search credits)
• Datasets: from $1,000

The math gets steep quickly. Ten thousand jobs per month puts you at the $800 Pro tier, which works out to $0.08 per job. If you need multi-source enriched records at 2 credits each, that doubles. For most use cases, Coresignal charges 2 to 10 times what alternatives charge for equivalent raw job data. The premium is justified if you need recruiter contact data and multi-source enrichment in a single call; it is not justified if you just want raw job listings.

What Coresignal does well:

• Vast LinkedIn coverage (349M+ LinkedIn job records)
• 14-day free trial with 200 Collect credits
• AI-ready datasets with MCP server integration
• GDPR and CCPA compliant
• Employee data alongside job data, which is unique among providers on this list

Limitations:

• Higher cost at every tier compared to alternatives
• Two-step API (search + collect) adds friction versus single-call providers
• No built-in UI for exploring data without writing code

Best for: Sales intelligence teams needing recruiter contacts alongside job data; enterprise customers who need LinkedIn enrichment at scale and have the budget to match.

3. TheirStack: Best for Multi-Source Coverage at Low Cost

TheirStack aggregates job postings from 315,000+ sources, including LinkedIn, Indeed, Glassdoor, and 16,000+ ATS platforms including Greenhouse, Lever, and Workable, and deduplicates them automatically. The database updates every minute. What TheirStack uniquely offers is the ability to filter jobs by company attributes: size, funding stage, industry, and tech stack. You can find “Series B fintech companies hiring ML engineers” without building the enrichment pipeline yourself. Understanding the underlying firmographic data that powers these filters helps explain why this capability is so valuable for sales-driven workflows.

Pricing:

• Free: 200 credits/month
• $59/month: 1,500 credits (~1,500 jobs)
• $169/month: 10,000 credits
• $400/month: 50,000 credits
• $1,500/month: 1,000,000 credits

At roughly $0.0015 to $0.039 per job depending on tier, TheirStack is among the cheapest options for multi-source coverage. Unused credits roll over for up to 12 months.

What makes TheirStack stand out:

• Near real-time updates every minute
• Built-in deduplication across all 315K sources
• Webhooks for real-time job alerts
• Filter jobs by company firmographics and tech stack in a single API call
• No-code web app for non-technical users

Limitations:

• No employee data alongside job listings
• Less established than Bright Data or Coresignal for enterprise procurement

Best for: Sales teams, job board builders, and developers who want broad coverage, low cost, and built-in deduplication without stitching together multiple providers.

4. Oxylabs: Best for Teams Building Custom Data Pipelines

Oxylabs sits in the same tier as Bright Data: a large infrastructure provider with dedicated job scraping products. Its datasets cover Indeed, Glassdoor, and StackShare, with delivery options via AWS S3, Google Cloud, Azure, and SFTP. The Jobs Web Scraper API supports custom parsers, a built-in web crawler, and the OxyCopilot assistant that converts natural language instructions into working API code in Python, Node.js, and more.

What Oxylabs offers:

• Standard job posting datasets from major job boards
• Custom datasets built to your specifications
• Dedicated account managers with Slack channel access
• One-week trial with 5K results for the Scraper API

Pricing:

• Standard Job Posting Datasets: from $1,000/month
• Scraper API: from $49/month ($2/1K results)
• Custom datasets: contact sales

Best for: Teams with engineering resources that need raw, unprocessed job data from specific sources, or organizations already using Oxylabs’ proxy infrastructure. If you are not already in the Oxylabs ecosystem, Bright Data offers comparable products with more job-specific coverage options.

5. SerpApi: Best for Google Jobs Data

SerpApi is primarily a SERP API provider, but its Google Jobs endpoint is worth calling out specifically. Google Jobs aggregates listings from thousands of sources including Indeed, LinkedIn, ZipRecruiter, and Workday, and SerpApi lets you pull that data programmatically. You get job title, company, location, description, apply links, salary (where Google displays it), and filters for employment type, date posted, and remote work.

Pricing:

• Free plan: 100 searches/month
• Starter: $25/month (500 searches)
• Developer: $75/month (5,000 searches)
• Production: $150/month (15,000 searches)
• Big Data: $275/month (30,000 searches)

What makes SerpApi useful:

• Hits Google’s aggregated job data, giving very broad source coverage by proxy
• Simple REST API with excellent documentation
• 99.977% uptime
• No infrastructure to manage

Limitations: You are limited to what Google Jobs surfaces, with no historical data, no bulk downloads, and no deduplication control. It works great for building job search features that mirror what Google shows. It is not a replacement for a dedicated job data provider if you need scale or custom filters.

Best for: Developers building job search features on a budget who need broad coverage quickly, or any application where “jobs Google knows about” is a sufficient data source. Bright Data’s own Google Search API is worth comparing if you need deeper SERP customization alongside job data.

6. LinkUp: Best for Clean Company-Sourced Enterprise Data

LinkUp has crawled directly from employer career pages since 2007, with no job boards and no LinkedIn scraping. The result is clean data with zero recruiter spam, no reposted jobs, and no duplicates across platforms. Their database holds 315M+ historical job postings across 195 countries, with approximately 5M daily active listings.

For quality-obsessed use cases like economic research, workforce forecasting, or hedge fund signal generation, LinkUp’s direct-source methodology matters. They maintain a “broken scrapes queue” that flags companies whose career pages have changed, typically restoring data within 24 hours for public companies.

Limitations: Enterprise-only with no self-serve option, no public pricing, and no free tier. Acquired by GlobalData in late 2024, which introduces some uncertainty about product direction. You will need to contact sales for a demo and custom quote.

Best for: Large enterprises and research institutions doing labor market analysis that require clean, direct-source data with long historical depth.

7. Revelio Labs: Best for Workforce Intelligence

Revelio Labs positions itself as a workforce intelligence platform rather than a job data API. Its COSMOS dataset covers 4.1B+ current and historical job postings from 6.6M companies, deduplicated and normalized with skills taxonomies, occupation classifications, and workforce dynamics data including headcount, hiring rates, and attrition rates by company and department.

This depth of enrichment goes far beyond what any other provider offers, but it is priced and packaged for institutional buyers. No self-serve access, no public pricing, and a demo is required to get started. Those evaluating this category of enriched data alongside employee insights may also find value in reviewing the best employee data providers as a complementary reference.

Best for: HR analytics teams, academic researchers, and corporate strategists who need workforce intelligence, not just raw job listings.

8. Techmap / jobdatafeeds.com: Best Budget Option for Historical Bulk Data

Techmap runs jobdatafeeds.com, providing job data feeds and historical datasets dating back to 2020. With approximately 6.7M new global job postings per month and an API priced at $1/1,000 jobs, it is among the most cost-effective options for volume. Historical datasets start at $2,400 per country.

Data formats include JSON, CSV, Parquet, XML, JSON-LD, and ATOM. A free trial and free dataset sample are available before you commit.

Best for: Budget-conscious developers and researchers who need historical data breadth and are comfortable with a less established provider.

How to Choose the Right Provider

Building a job board or aggregator: Bright Data datasets for the initial bulk load, TheirStack or Bright Data’s dedicated Scraper APIs for ongoing fresh listings. TheirStack’s built-in deduplication saves meaningful engineering time if your board pulls from many sources.

Doing sales intelligence: TheirStack’s company attribute filters (industry, funding, tech stack) are uniquely powerful here. Bright Data works well at scale. Coresignal adds value when recruiter contact data is important to your workflow. For a broader view of this space, see the guide to the best B2B data providers.

Need LinkedIn-specific data at scale: Coresignal or Bright Data’s LinkedIn datasets and scrapers. Coresignal goes deeper on enrichment; Bright Data is more cost-effective at high volume and offers broader delivery options. The top LinkedIn scraping tools guide covers the full spectrum of options for this use case.

Training an AI model: Bright Data’s AI-ready data packages with LLM-optimized formatting and native integrations for LangChain, CrewAI, and LlamaIndex. Coresignal also explicitly supports AI/ML workflows.

Running labor market research: LinkUp for clean direct-source historical data going back to 2007. Revelio Labs if you need workforce dynamics (headcount, attrition) alongside raw job postings. Bright Data’s Web Archive offers 50PB+ of historical data as an alternative source for longitudinal research.

On a tight budget: TheirStack’s free tier (200 credits/month) is genuinely usable for prototyping. SerpApi’s 100 free searches cover small experiments. For paid production use at minimum cost, TheirStack at $59/month offers the best breadth per dollar.

Already using a scraping infrastructure provider: Stick with Bright Data or Oxylabs for job data. You get easier integration, an existing account relationship, and a single vendor for infrastructure and data products.

Final Verdict

No single provider wins for every use case.

Bright Data is the most versatile option. It covers the most sources, offers every delivery model (API, scraper, dataset, custom), integrates with 70+ tools, and provides enterprise-grade compliance with ISO 27001 certification. If you are unsure exactly what you need, Bright Data’s ecosystem lets you start with a dataset and scale to real-time scraping without switching vendors. Start with the free trial to validate coverage before committing.

TheirStack is the best value play for developers and sales teams who want multi-source coverage, built-in deduplication, and near real-time freshness without paying enterprise prices.

Coresignal is the right call when you specifically need LinkedIn depth plus employee enrichment and are comfortable paying a premium for cleaner, richer data out of the box.

SerpApi is the fastest path to Google Jobs data if you are building a job search feature and do not need historical access or dataset downloads.

Match the provider to the use case, validate with free samples before committing to scale, and do not underestimate the engineering cost of managing everything yourself.

Frequently Asked Questions

What is the difference between a job API and a job dataset?
APIs let you query job data in real time per request. Datasets are bulk exports of millions of records delivered to your storage. APIs suit dynamic applications; datasets suit bulk processing and deliver lower per-record cost at scale.

How much does a job API cost?
Free tiers exist at TheirStack (200 credits/month) and SerpApi (100 searches/month). Paid access ranges from $25/month for SerpApi’s Starter plan to $800/month for Coresignal’s Pro tier. Bright Data’s Scraper APIs start at $0.75/1K records on subscription. Dataset pricing varies by volume.

Can I get historical job data?
Yes. Bright Data’s Web Archive provides 50PB+ of historical data. TheirStack archives go back to 2021. LinkUp goes back to 2007. Revelio Labs to 2008. Techmap to 2020. The right choice depends on how far back you need to go and whether you need raw listings or enriched workforce data.

How long does integration take?
A basic API integration (auth, first request, parsed response) takes minutes with good documentation. Production-ready integration covering error handling, rate limit management, caching, and schema normalization typically takes one to two weeks. Dataset integration (download to S3, load to database) can often be done in a single day with standard cloud tooling.