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v10

latestOpenAPI 3.1.02026-08-0452108384.4 KB
Jobs

Job Search

Search and filter job postings (job ads, vacancies, hiring data) from thousands of company career sites and job boards. Filter by job title, keywords in the job description, company (name, domain or LinkedIn URL), location and country, technology and tech stack, salary, seniority, remote/hybrid, employment type, and posting date. Used for sales prospecting and lead generation, recruiting, and hiring-trend and market research.

It consumes 1 API credit for each job returned in the response.

You must specify at least one of the following filters, or otherwise your request will fail: posted_at_max_age_days, posted_at_gte, posted_at_lte, company_domain_or, company_linkedin_url_or, company_name_or. This is for performance reasons.

To retrieve jobs from a specific company or a list of companies, you can apply any of the following filters: company_domain_or, company_linkedin_url_or, company_name_or, company_name_case_insensitive_or. When using multiple company identifier filters, the endpoint will return jobs from companies that match any of the specified identifiers. Therefore, it is advisable to create a separate request for each company if you intend to use more than one identifier.

company_linkedin_url_or accepts both forms of LinkedIn company URL — the vanity slug (https://www.linkedin.com/company/google/) and the numeric company ID (https://www.linkedin.com/company/1038) — as well as a bare slug (google) or a bare numeric ID (1038). A numeric value is matched against the company's LinkedIn ID and its slug, so you do not need to know which of the two you are holding. Coverage differs by identifier: we have a domain for ~29% of companies, a LinkedIn slug for ~26% and a numeric LinkedIn ID for ~14%, so prefer company_domain_or when you have the company's domain.

This endpoint is used by job seekers and sales/marketing teams to search for jobs filtered by country, job title, technologies, job description, company name, company domain, or date range—see the payload examples below for specific use cases.

Useful resources: Avoiding getting the same job twice, Fetching jobs periodically, Preview data mode, Free count mode

post/v1/jobs/search

Request body

offsetinteger

Number of results to skip. Required for offset-based pagination.

pageinteger

Page number. Required when using page-based pagination.

limitinteger

Number of results per page

cursorstring nullable

Cursor for pagination

job_title_orstring[]

Keyword-based patterns to match job titles. Case-insensitive. Returns jobs whose title contains all the words in any of the patterns, in any order. For example, marketing vp matches titles such as VP of Marketing or Marketing VP, EMEA. Passing ["software engineer", "data scientist"] returns jobs matching either pattern.

job_title_notstring[]

Keyword-based patterns to exclude job titles. Case-insensitive. Excludes jobs whose title contains all the words in any of the patterns, in any order. For example, marketing vp excludes titles such as VP of Marketing or Marketing VP, EMEA.

job_title_pattern_andstring[]

Regex patterns to match job titles. Case-insensitive. Only jobs with title that match all of these patterns will be returned.

job_title_pattern_orstring[]

Regex patterns to match job titles. Case-insensitive. Jobs whose job title matches of the filters will be returned.

job_title_pattern_notstring[]

Regex patterns to match job titles. Case-insensitive. Jobs whose job title doesn't match any of the patterns will be returned.

job_country_code_orstring[]

2-letter ISO country code of the location of the job. Can pass more than 1

job_country_code_notstring[]

2-letter ISO country code of the location of the job. Can pass more than 1. Will exclude jobs from these countries

posted_at_max_age_daysinteger nullable

Date posted max age in days. If 0, only return jobs posted today. If 1, from today and yesterday, etc.

posted_at_gtestring date nullable

ISO 8601 date string (yyyy-mm-dd). Only jobs published in this date or after will be returned.

posted_at_ltestring date nullable

ISO 8601 date string (yyyy-mm-dd). Only jobs published in this date or before will be returned.

discovered_at_max_age_daysinteger nullable

If 0, only return jobs added to our database in the current day. If 1, from today and yesterday, etc.

discovered_at_min_age_daysinteger nullable

If 1, only return jobs discovered by TheirStack until yesterday. If 2, until 2 days ago, etc.

job_description_pattern_orstring[]

Regex patterns to look for in job descriptions. Case-sensitive. Results will include jobs whose description matches any of these patterns. Use (?i) at the start of a pattern to make it case-insensitive. Can pass more than one.

job_description_pattern_notstring[]

Regex patterns to look for in job descriptions. Case-sensitive. Results will include jobs whose description don't match any of these patterns. Use (?i) at the start of a pattern to make it case-insensitive. Can pass more than one.

job_description_pattern_andstring[]

Regex patterns that must ALL match the job description (AND logic). Use (?i) at the start of a pattern to make it case-insensitive. Results will only include jobs whose description matches every pattern in this list.

job_description_pattern_is_case_insensitiveboolean nullable

Deprecated. Has no effect.

job_description_contains_orstring[]

Search for whole words in job descriptions using word boundaries (\b). Case-insensitive by default, except for the patterns that are uppercase - in that case we'll respect it. Only finds complete words (e.g., searching 'quality' won't match 'inequality'). Results will include jobs whose description contains any of these words.

job_description_contains_notstring[]

Exclude jobs whose description contains any of these whole words using word boundaries (\b). Case-insensitive by default, except for the patterns that are uppercase - in that case we'll respect it. Only finds complete words (e.g., searching 'quality' won't match 'inequality'). Results will exclude jobs whose description contains any of these words.

job_description_pattern_case_sensitive_orstring[]

Deprecated. Use job_description_pattern_or instead, which now behaves identically.

remoteboolean nullable

True: only show remote jobs. False: only show non-remote jobs. None: show all jobs.

only_jobs_with_reports_toboolean nullable

Only return jobs where we identified the role the hired person would report to. Deprecated field, use reports_to_exists instead.

reports_to_existsboolean nullable

Only return jobs where we identified the role the hired person would report to. If True, only return jobs where we identified the role the hired person would report to. If False, only return jobs where we didn't identify the role the hired person would report to. If None, return all jobs.

final_url_existsboolean nullable

(Use property_exists_or / property_exists_and instead) Only return jobs with a final URL. Typically jobs that were originally posted on an ATS. If True, only return jobs with a final URL. If False, only return jobs without a final URL. If None, return all jobs.

only_jobs_with_hiring_managersboolean nullable

Only return jobs with a hiring manager. If True, only return jobs with a hiring manager. If False, only return jobs without a hiring manager. If None, return all jobs.

hiring_managers_existsboolean nullable

(Use property_exists_or / property_exists_and instead) If True, only return jobs with a hiring manager. If False, only return jobs without a hiring manager. If None, return all jobs.

job_id_orinteger[]

Get jobs with these IDs only.

job_id_notinteger[]

Exclude jobs with these IDs.

job_idsinteger[]

Get jobs with these IDs only. Deprecated parameter, use job_id_or instead.

job_seniority_orstring[]

Will return jobs where the seniority is any of the ones passed here

min_salary_usdnumber nullable

Minimum annual salary in USD. For example, 100000 means $100,000.

max_salary_usdnumber nullable

Maximum annual salary in USD. For example, 150000 means $150,000.

job_technology_slug_orstring[]

Will return jobs where any of these technologies appear. Case sensitive. Pass slugs. Check out all the technologies we track with the technologies endpoint. If you pass more than one technology, we will return jobs that mentnion all of the technologies.

job_technology_slug_notstring[]

Will return jobs where none of these technologies appear. Case sensitive. Pass slugs. Check out all the technologies we track with the technologies endpoint.

job_technology_slug_andstring[]

Will return jobs where all of these technologies appear. Case sensitive. Pass slugs. Check out all the technologies we track with the technologies endpoint.

job_keyword_slug_orstring[]

Will return jobs where any of these keyword slugs appear. Case sensitive. Check out all the keywords we track at GET /v0/catalog/keywords

job_keyword_slug_andstring[]

Will return jobs where all of these keyword slugs appear. Case sensitive. Check out all the keywords we track at GET /v0/catalog/keywords

job_keyword_slug_notstring[]

Will return jobs where none of these keyword slugs appear. Case sensitive. Check out all the keywords we track at GET /v0/catalog/keywords

job_location_pattern_orstring[]

Regex patterns to match job locations. Case-insensitive. Searches both the location field and the enhanced locations array (using normalized city and state name fields within each location element). Jobs matching ANY of the provided patterns will be returned.

WARNING: Deprecated parameter. Use the job_location_or filter instead — it uses structured location IDs from the locations catalog, which is more precise, supports hierarchical (country/region/city) and multi-language searches, has fewer false positives, and benefits from indexed lookups and recent accuracy fixes.

job_location_pattern_notstring[]

Regex patterns to exclude job locations. Case-insensitive. Searches both the location field and the enhanced locations array (using normalized city and state name fields within each location element). Jobs matching ANY of the provided patterns will be EXCLUDED from results.

WARNING: Deprecated parameter. Use the job_location_not filter instead — it uses structured location IDs from the locations catalog, which is more precise, supports hierarchical (country/region/city) and multi-language searches, has fewer false positives, and benefits from indexed lookups and recent accuracy fixes.

url_domain_orstring[]

Include jobs only if their URL domain (from url or source_url) is in the provided case-insensitive list. For example, ['greenhouse.io', 'workable.com'] will match URLs containing 'greenhouse.io' or 'workable.com'. Refer to our list of sources at https://theirstack.com/en/docs/data/job/sources.

url_domain_notstring[]

Exclude jobs if their URL domain (from url or source_url) is in the provided case-insensitive list. For example, ['greenhouse.io', 'workable.com'] will exclude URLs containing 'greenhouse.io' or 'workable.com'. Refer to our list of sources at https://theirstack.com/en/docs/data/job/sources.

scraper_name_pattern_orstring[]

Regex patterns to match job sources. Case-insensitive.

easy_applyboolean nullable

If True, only return jobs that can be applied directly through the job board. If False, only return jobs that require redirecting to the company's website.

employment_statuses_orCommitment[] nullable

Filter jobs by employment status. Returns jobs that match any of the specified employment types. If no values are provided or an empty list is sent, all jobs regardless of employment status will be returned.

is_closedboolean nullable

If True, only return closed jobs (jobs where TheirStack detected the posting was closed). If False, only return open jobs. If None, return all jobs regardless of closure status.

closed_at_gtestring date nullable

ISO 8601 date string (yyyy-mm-dd). Only return jobs closed on this date or after.

closed_at_ltestring date nullable

ISO 8601 date string (yyyy-mm-dd). Only return jobs closed on this date or before.

property_exists_orstring[]

Return jobs that have any of these fields not null. For example, if you pass ['final_url'], it will return jobs that have a final_url set. This field also support chaining of fields. For example, if you pass ['company_object.domain', 'company_object.linkedin_url'], it will return jobs that have a company domain or a company linkedin_url set.

property_exists_andstring[]
company_name_orstring[]

Only return companies that match these names exactly, case-sensitively. This filter acts as an OR filter, so if you pass more than one company name, it will return companies that match any of the names.

company_name_case_insensitive_orstring[]

Only return companies that match these names exactly, case-insensitively.

company_id_orstring[]

Only return companies that match these IDs exactly. This filter acts as an OR filter, so if you pass more than one company ID, it will return companies that match any of the IDs.

company_id_notstring[]

Exclude companies that match these IDs. This filter acts as a NOT filter, so if you pass more than one company ID, it will exclude companies that match any of the IDs.

company_domain_orstring[]

Only return companies that match these domains exactly. It accepts full urls (https://www.google.com/) and emails (john.polo@gmail.com). This filter acts as an OR filter, so if you pass more than one company domain, it will return companies that match any of the domains.

company_domain_notstring[]

Only return companies that don't match these domains exactly. It accepts full urls (https://www.google.com/) and emails (john.polo@gmail.com).

company_name_notstring[]

Only return companies that don't match these names exactly, case-sensitively.

company_name_partial_match_orstring[]

Company names. Will return companies whose name contain any of the the substrings passed here, case-insensitively. For example, if you pass "google", it will return "Google", "Google LLC", "Google Inc", etc.

company_name_partial_match_notstring[]

Company names. Will return companies whose name doesn't contain any of the the substrings passed here, case-insensitively. For example, if you pass 'google', it will exclude 'Google', 'Google LLC', 'Google Inc', etc.

company_linkedin_url_orstring[]

Return companies whose LinkedIn page matches any of the values passed here. Both forms of LinkedIn company URL work — the vanity slug (https://www.linkedin.com/company/google/) and the numeric company ID (https://www.linkedin.com/company/1038) — as do a bare slug (google) and a bare numeric ID (1038). A numeric value is matched against the company's LinkedIn ID and its slug, so you do not need to know which of the two you are holding. We have a LinkedIn slug for ~26% of companies and a numeric LinkedIn ID for ~14%, so if you have the company's domain, company_domain_or matches more often.

blur_company_databoolean

Enable preview mode to return blurred data without consuming API credits. When enabled, sensitive company fields (name, domain, URLs, descriptions) and job-specific fields (description, URLs) are blurred. This mode is useful for sales software integrations to show data previews to end users. Not available when filtering by company identifiers (company_name, company_domain, company_linkedin_url, company_id). Learn more about here

company_description_pattern_orstring[]

Case-insensitive patterns to match in the company description. Will return companies that match any of the patterns.

company_description_pattern_notstring[]

Case-insensitive patterns to match in the company description. Will return companies that match any of the patterns.

company_description_pattern_accent_insensitiveboolean nullable

Set to True to make company description searches accent insensitive. For example, "á" will match "a" as well.

min_revenue_usdinteger nullable

Minimum company revenue, in USD

max_revenue_usdinteger nullable

Maximum company revenue, in USD

min_employee_countinteger nullable

Minimum number of employees in a company

max_employee_countinteger nullable

Maximum number of employees in a company

min_employee_count_or_nullinteger nullable

Minimum number of employees in a company. If we don't have company size information, we will return it as well.

max_employee_count_or_nullinteger nullable

Maximum number of employees in a company. If we don't have company size information, we will return it as well.

min_funding_usdinteger nullable

Minimum company funding, in USD

max_funding_usdinteger nullable

Maximum company funding, in USD

funding_stage_orstring[]

Funding stages of companies returned. Possible values: ['angel', 'convertible_note', 'debt_financing', 'equity_crowdfunding', 'other', 'private_equity', 'seed', 'series_a', 'series_b', 'series_c', 'series_d', 'series_e', 'series_f', 'series_g', 'series_h', 'venture_round_not_specified', 'series_i', 'series_j', 'undisclosed', 'series_unknown', 'pre_seed', 'post_ipo_secondary', 'post_ipo_equity', 'post_ipo_debt', 'non_equity_assistance', 'late_vc', 'initial_coin_offering', 'growth_equity_vc', 'grant', 'early_vc', 'corporate_round', 'secondary_market', 'product_crowdfunding']

industry_orstring[]

Names of industries, case-insensitive. Results will only include companies that belong to any of the industries specified in this parameter. Available values: GET /v0/catalog/industries

WARNING: Deprecated parameter. Use the industry_id_or field instead.
industry_notstring[]

Names of industries, case-insensitive. Results will exclude companies that belong to any of the industries specified in this parameter. Available values: GET /v0/catalog/industries

WARNING: Deprecated parameter. Use the industry_id_not field instead.
industry_id_orinteger[]

Industry codes. You can use any of LinkedIn's Industry Codes V2 or GET /v0/catalog/industries

industry_id_notinteger[]

Industry ids to exclude.You can use any of LinkedIn's Industry Codes V2 or GET /v0/catalog/industries

industry_id_not_or_nullinteger[]

Industry ids to exclude. Companies whose industry we don't know are returned as well. You can use any of LinkedIn's Industry Codes V2 or GET /v0/catalog/industries

company_tags_orstring[]

Return companies that match any of these keywords

company_type'recruiting_agency' | 'direct_employer' | 'all' nullable

Filter by company type.

company_investors_orstring[]

Investors of the company

company_investors_partial_match_orstring[]

Investors of the company. Will return companies for which any of their investors contains any of the substrings passed here. For example, if you pass 'andree', all funds that match it (like 'Andreessen Horowitz', 'Andreessen Horowitz LLC', etc).

company_technology_slug_orstring[]

Will return jobs from companies that that have mentioned any of these technologies in their jobs (not necessarily in the jobs returned). Case sensitive. Pass slugs. Check out all the technologies we track at GET /v0/catalog/technologies

company_technology_slug_andstring[]

Will return jobs from companies that that have mentioned all of these technologies in their jobs (not necessarily in the jobs returned). Case sensitive. Pass slugs. Check out all the technologies we track at GET /v0/catalog/technologies

company_technology_slug_notstring[]

Will return jobs from companies that that haven't mentioned any of these technologies in their jobs. Case sensitive. Pass slugs. Check out all the technologies we track at GET /v0/catalog/technologies

company_keyword_slug_orstring[]

Return results from companies that have mentioned any of these keywords in their jobs. Case sensitive. Pass slugs. Check out all the keywords we track at GET /v0/catalog/keywords

company_keyword_slug_andstring[]

Return results from companies that have mentioned all of these keywords in their jobs. Case sensitive. Pass slugs. Check out all the keywords we track at GET /v0/catalog/keywords

company_keyword_slug_notstring[]

Return results from companies that haven't mentioned any of these keywords in their jobs. Case sensitive. Pass slugs. Check out all the keywords we track at GET /v0/catalog/keywords

only_yc_companiesboolean nullable

Only return YC companies

company_location_pattern_orstring[]

Return companies whose city matches any of the patterns passed here. Case insensitive. For example, if you pass 'san francisco', it will return companies whose city is 'San Francisco', 'San Francisco Bay Area', etc.

company_country_code_orstring[]

Return companies whose HQ country code is any of the ones passed here, case sensitive. Pass ISO2 country codes.

company_country_code_notstring[]

Return companies whose HQ country code is not any of the ones passed here, case sensitive. Pass ISO2 country codes.

company_country_code_not_or_nullstring[]

Return companies whose HQ country code is not any of the ones passed here, case sensitive. Companies whose country we don't know are returned as well. Pass ISO2 country codes.

company_list_id_orinteger[]

Return companies that belong to any of the company lists passed here

company_list_id_notinteger[]

Return companies that don't belong to any of the company lists passed here

company_linkedin_url_existsboolean nullable

(Use property_exists_or / property_exists_and instead) Only return companies with a LinkedIn URL

revealed_company_databoolean nullable

This field is deprecated and has no effect.

last_funding_round_date_ltestring date nullable

Only return companies whose last funding round date is before or on this date. Format: 'YYYY-MM-DD'

last_funding_round_date_gtestring date nullable

Only return companies whose last funding round date is after or on this date. Format: 'YYYY-MM-DD'

include_total_resultsboolean

When enabled, calculates and returns total_results and total_companies fields in the response. WARNING: This significantly slows down responses as it requires reading the entire dataset. Recommended usage: enable only for the initial request to get totals, then disable for subsequent pagination requests.

Example request

{
  "limit": 25,
  "job_title_or": [],
  "job_title_not": [],
  "job_title_pattern_and": [],
  "job_title_pattern_or": [],
  "job_title_pattern_not": [],
  "job_country_code_or": [],
  "job_country_code_not": [],
  "job_description_pattern_or": [],
  "job_description_pattern_not": [],
  "job_description_pattern_and": [],
  "job_description_contains_or": [],
  "job_description_contains_not": [],
  "job_description_pattern_case_sensitive_or": [],
  "job_id_or": [],
  "job_id_not": [],
  "job_seniority_or": [],
  "job_location_pattern_or": [],
  "job_location_pattern_not": [],
  "job_location_or": [],
  "job_location_not": [],
  "url_domain_or": [],
  "url_domain_not": [],
  "employment_statuses_or": [],
  "property_exists_or": [],
  "property_exists_and": [],
  "company_name_or": [],
  "company_name_case_insensitive_or": [],
  "company_id_or": [],
  "company_id_not": [],
  "company_domain_or": [],
  "company_domain_not": [],
  "company_name_not": [],
  "company_name_partial_match_or": [],
  "company_name_partial_match_not": [],
  "company_linkedin_url_or": []
}

Response

Successful Response

Example response

{
  "metadata": {
    "total_results": 2034,
    "total_companies": 1045
  },
  "data": [
    {
      "id": 1234,
      "job_title": "Senior Data Engineer",
      "url": "https://example.com/job/1234",
      "date_posted": "2021-01-01",
      "company": "Google",
      "final_url": "https://carecrafterhealth.com/careers/job-details/MFC286442-4",
      "source_url": "https://www.linkedin.com/jobs/view/1234567890",
      "location": "New York",
      "short_location": "Tulsa, OK",
      "long_location": "Methuen, MA 01844",
      "state_code": "OK",
      "latitude": 37.774929,
      "longitude": -96.726486,
      "postal_code": "01844",
      "remote": true,
      "hybrid": true,
      "salary_string": "$100,000 - $120,000",
      "min_annual_salary": 100000,
      "min_annual_salary_usd": 100000,
      "max_annual_salary": 100000,
      "max_annual_salary_usd": 100000,
      "avg_annual_salary_usd": 100000,
      "salary_currency": "USD",
      "countries": [
        "United States",
        "Canada",
        "Spain",
        "France",
        "Australia"
      ],
      "country": "United States",
      "country_codes": [
        "US",
        "CA",
        "ES",
        "FR",
        "AU"
      ],
      "country_code": "US",
      "cities": [
        "New York",
        "San Francisco",
        "London",
        "Paris",
        "Sydney"
      ],
      "continents": [
        "North America",
        "Europe",
        "Asia",
        "Australia",
        "South America"
      ],
      "discovered_at": "2024-01-01T00:00:00",
      "closed_at": "2024-06-15T12:30:00Z",
      "company_domain": "acme.com",
      "hiring_team": [
        {
          "first_name": "John Doe",
          "full_name": "John Doe",
          "image_url": "https://media.licdn.com/dms1234567890",
          "linkedin_url": "https://www.linkedin.com/in/john-doe-1234567890",
          "role": "CEO",
          "thumbnail_url": "https://media.licdn.com/dms1234567890"
        }
      ],
      "reposted": true,
      "date_reposted": "2024-01-01",
      "employment_statuses": [
        "full_time"
      ],
      "easy_apply": true,
      "technology_slugs": [
        "google-firebase",
        "postgresql",
        "jira"
      ],
      "keyword_slugs": [
        "google-firebase",
        "postgresql",
        "lead-generation"
      ],
      "description": "## About the Role\nWe are looking for a Senior Data Engineer with 5+ years of experience in data engineering to join our growing data team. You will be responsible for designing and implementing scalable data pipelines, data models, and data warehouses that support our business intelligence and analytics initiatives.\n\n## Key Responsibilities\n- Design, build, and maintain robust, scalable data pipelines using modern data engineering tools and frameworks\n- Develop and optimize data models and schemas for data warehouses and data lakes\n- Collaborate with data scientists, analysts, and product teams to understand data requirements and deliver solutions\n- Implement data quality monitoring and validation processes to ensure data accuracy and reliability\n- Optimize query performance and data processing workflows for large-scale datasets\n- Build and maintain ETL/ELT processes using tools like Apache Airflow, dbt, or similar\n- Work with cloud data platforms (AWS, GCP, or Azure) and their native data services\n- Establish data governance practices and ensure compliance with data privacy regulations\n- Mentor junior data engineers and contribute to technical documentation\n\n## Required Qualifications\n- Bachelor's degree in Computer Science, Engineering, or related technical field\n- 5+ years of experience in data engineering or related roles\n- Strong proficiency in Python and SQL\n- Experience with big data technologies (Spark, Kafka, Hadoop ecosystem)\n- Hands-on experience with cloud data platforms (AWS Redshift, GCP BigQuery, Azure Synapse, etc.)\n- Experience with data orchestration tools (Airflow, Prefect, or similar)\n- Knowledge of data modeling concepts and best practices\n- Experience with version control systems (Git) and CI/CD pipelines\n- Strong problem-solving skills and attention to detail\n\n## Preferred Qualifications\n- Experience with real-time data processing and streaming analytics\n- Knowledge of data visualization tools (Tableau, Looker, PowerBI)\n- Experience with containerization (Docker, Kubernetes)\n- Familiarity with machine learning workflows and MLOps practices\n- Experience with data governance and cataloging tools\n\n## What We Offer\n- Competitive salary and equity package\n- Comprehensive health, dental, and vision insurance\n- Flexible work arrangements and remote-friendly culture\n- Professional development budget for conferences and training\n- State-of-the-art equipment and technology stack\n- Collaborative and inclusive work environment\n- Opportunity to work with cutting-edge data technologies",
      "company_object": {
        "id": "google",
        "name": "Google",
        "domain": "google.com",
        "industry": "internet",
        "country": "United States",
        "employee_count": 7543,
        "logo": "https://example.com/logo.png",
        "num_jobs": 746,
        "num_technologies": 746,
        "url": "google.com",
        "linkedin_url": "http://www.linkedin.com/company/google",
        "num_jobs_last_30_days": 34,
        "num_jobs_found": 23,
        "yc_batch": "W21",
        "apollo_id": "5b839bd0324d4445051f9a5a",
        "founded_year": 2019,
        "annual_revenue_usd": 189000000,
        "annual_revenue_usd_readable": "189M",
        "total_funding_usd": 500000,
        "last_funding_round_date": "2020-01-01",
        "last_funding_round_amount_readable": "$1.2M",
        "employee_count_range": "1001-5000",
        "long_description": "Google is a California-based multinational technology company that offers internet-related services such as a search engine, online advertising and cloud computing.",
        "city": "Mountain View",
        "postal_code": "28040",
        "alexa_ranking": 1,
        "publicly_traded_symbol": "GOOG",
        "publicly_traded_exchange": "NASDAQ",
        "keyword_slugs": [
          "kafka",
          "elasticsearch",
          "lead-generation"
        ],
        "technology_slugs": [
          "kafka",
          "elasticsearch"
        ],
        "technology_names": [
          "Kafka",
          "Elasticsearch"
        ]
      },
      "locations": [
        {
          "admin1_code": "CA",
          "admin1_name": "California",
          "admin2_code": "101",
          "admin2_name": "Sutter",
          "continent": "NA",
          "country_code": "US",
          "country_name": "United States",
          "display_name": "Live Oak, California, United States",
          "feature_code": "PPL",
          "id": 5367315,
          "latitude": 37,
          "longitude": -122,
          "name": "Live Oak",
          "state": "California",
          "state_code": "CA",
          "type": "city"
        }
      ]
    }
  ]
}