As of 2024, 7.5 percent of U.S. Google employees were of Hispanic or Latinx ethnicity. The biggest share of Google employees were white. Currently, more than four in ten Google employees were white, down from more than six in ten in 2014.

In 2024, 4.3 percent of U.S. Google leadership employees were of Latinx ethnicity. The majority of leadership employees, about six in ten, were white. Asian Google employees accounted for the second-largest group of employees in leadership positions.

This dataset contains current and historical demographic data on Google's workforce since the company began publishing diversity data in 2014. It includes data collected for government reporting and voluntary employee self-identification globally relating to hiring, retention, and representation categorized by race, gender, sexual orientation, gender identity, disability status, and military status. In some instances, the data is limited due to various government policies around the world and the desire to protect Googler confidentiality. All data in this dataset will be updated yearly upon publication of Google’s Diversity Annual Report . Google uses this data to inform its diversity, equity, and inclusion work. More information on our methodology can be found in the Diversity Annual Report. This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

As of January 2024, the majority of Google employees worldwide, almost 66 percent, were male. The distribution of male and female employees at Google hasn’t seen a big change over the recent years. In 2014 the share of female employees at Google was 30.6 percent. In 2021 this number has increased by only 3 percent. Considering that the total number of Google employees increased greatly between the years 2007 and 2020, the female quota among the employees had seen rather a small increase. Google as a company Google is a diverse internet company that provides a wide range of digital products and services. In 2022, the company’s global revenue was over 279 billion U.S. dollars. Most of its revenue, around 305 billion U.S. dollars, was from advertising. Among its services, the most popular ones are YouTube and Google Play. Male and female employees at tech companies Google is not the only tech company with a lower number of female employees. This pattern can be seen in other big tech companies too. In 2019, in a ranking of 20 leading tech companies worldwide, only 23andMe had more than a 50 percent share of female employees. The majority of tech companies in the ranking have far more male than female employees.

In 2024, the share of female Google employees worldwide in leadership positions amounted to 32.8 percent. The majority of leadership employees were men. Overall, about two thirds of Google employees worldwide were male.

At the end of 2024, Alphabet had 183,323 full-time employees. Up until 2015, these figures were reported as Google employees. The alphabet was created through a corporate restructuring of Google in October 2015 and became the parent company of Google as well as several of its former subsidiaries, including Calico, X, CapitalG and Sidewalk Labs. Google’s popularity Google is one of the most famous internet companies in the world, and in May 2024, the most visited multi-platform website in the United States, with over 278 million U.S. unique visitors during that month alone. The California-based multinational internet company has been delivering digital products and services since its creation in 1996. Due to the popularity of its search engine, the verb “to google” has entered the everyday language and the Oxford Dictionary. In addition to that, the company has also crafted itself as one of the most desirable employers, largely due to the many perks it offers in its offices worldwide. Some of the most appealing aspects of working for Google according to its employees include readily available foods and drinks, good working conditions, and ample communal spaces for relaxing, as well as many health benefits and generous salaries. Google offices and employees As of February 2022, Google and Alphabet had more than 70 offices in over 200 cities throughout 50 around the globe, including Germany, Czechia, Finland, Canada, Mexico, Turkey, and New Zealand. The company’s headquarters, also known as “the Googleplex,” are located in Mountain View, California, while other office locations in American states include New York, Georgia, Texas, Washington D.C., and Massachusetts. As Alphabet, the company employs a total over 182 thousand full-time staff, in addition to many other temporary and internship positions. Per the most recent diversity report published in July 2021, most Google employees were male and only 34 percent were female – a figure that has barely changed since the company started reporting on the diversity of its employees in 2016. Furthermore, as of 2021, women occupied only 28.1 percent of leadership positions and 24.6 percent of tech positions. Although Google has regularly stated that the company is committed to promoting ethnic diversity among its personnel, some 54.4 percent of its U.S. employees are White and only 3.3 percent of employees are Black.

Diversity in Tech Statistics: In today's tech-driven world, discussions about diversity in the technology sector have gained significant traction. Recent statistics shed light on the disparities and opportunities within this industry. According to data from various sources, including reports from leading tech companies and diversity advocacy groups, the lack of diversity remains a prominent issue. For example, studies reveal that only 25% of computing jobs in the United States are held by women, while Black and Hispanic individuals make up just 9% of the tech workforce combined. Additionally, research indicates that LGBTQ+ individuals are underrepresented in tech, with only 2.3% of tech workers identifying as LGBTQ+. Despite these challenges, there are promising signs of progress. Companies are increasingly recognizing the importance of diversity and inclusion initiatives, with some allocating significant resources to address these issues. For instance, tech giants like Google and Microsoft have committed millions of USD to diversity programs aimed at recruiting and retaining underrepresented talent. As discussions surrounding diversity in tech continue to evolve, understanding the statistical landscape is crucial in fostering meaningful change and creating a more inclusive industry for all. Editor’s Choice In 2021, 7.9% of the US labor force was employed in technology. Women hold only 26.7% of tech employment, while men hold 73.3% of these positions. White Americans hold 62.5% of the positions in the US tech sector. Asian Americans account for 20% of jobs, Latinx Americans 8%, and Black Americans 7%. 83.3% of tech executives in the US are white. Black Americans comprised 14% of the population in 2019 but held only 7% of tech employment. For the same position, at the same business, and with the same experience, women in tech are typically paid 3% less than men. The high-tech sector employs more men (64% against 52%), Asian Americans (14% compared to 5.8%), and white people (68.5% versus 63.5%) compared to other industries. The tech industry is urged to prioritize inclusion when hiring, mentoring, and retaining employees to bridge the digital skills gap. Black professionals only account for 4% of all tech workers despite being 13% of the US workforce. Hispanic professionals hold just 8% of all STEM jobs despite being 17% of the national workforce. Only 22% of workers in tech are ethnic minorities. Gender diversity in tech is low, with just 26% of jobs in computer-related sectors occupied by women. Companies with diverse teams have higher profitability, with those in the top quartile for gender diversity being 25% more likely to have above-average profitability. Every month, the tech industry adds about 9,600 jobs to the U.S. economy. Between May 2009 and May 2015, over 800,000 net STEM jobs were added to the U.S. economy. STEM jobs are expected to grow by another 8.9% between 2015 and 2024. The percentage of black and Hispanic employees at major tech companies is very low, making up just one to three percent of the tech workforce. Tech hiring relies heavily on poaching and incentives, creating an unsustainable ecosystem ripe for disruption. Recruiters have a significant role in disrupting the hiring process to support diversity and inclusion. You May Also Like To Read Outsourcing Statistics Digital Transformation Statistics Internet of Things Statistics Computer Vision Statistics

In the fiscal period that ended December 31, 2023, Google UK Limited's average number of employees was 7,442 employees. This was a slight increase compared to the previous reporting period ending December 31, 2022, where 7,005 individuals were reported to have had worked for the company in the UK.

Context

The Bureau of Labor Statistics (BLS) is a unit of the United States Department of Labor. It is the principal fact-finding agency for the U.S. government in the broad field of labor economics and statistics and serves as a principal agency of the U.S. Federal Statistical System. The BLS is a governmental statistical agency that collects, processes, analyzes, and disseminates essential statistical data to the American public, the U.S. Congress, other Federal agencies, State and local governments, business, and labor representatives. Source: https://en.wikipedia.org/wiki/Bureau_of_Labor_Statistics

Content

Bureau of Labor Statistics including CPI (inflation), employment, unemployment, and wage data.

Update Frequency: Monthly

Querying BigQuery Tables

Fork this kernel to get started.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:bls

https://cloud.google.com/bigquery/public-data/bureau-of-labor-statistics

Dataset Source: http://www.bls.gov/data/

This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

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Inspiration

What is the average annual inflation across all US Cities? What was the monthly unemployment rate (U3) in 2016? What are the top 10 hourly-waged types of work in Pittsburgh, PA for 2016?

In 2023, Amazon.com was the top-ranked internet company based on number of employees. The e-commerce giant reported a workforce of more than **** million employees. Amazon has consistently topped the ranking as the online company with the biggest workforce, but the global COVID-19 pandemic has widened the gap as e-commerce has boomed since. During the same period, Meta (formerly Facebook Inc.) had a total of ****** full-time employees. Additionally, Google's parent company Alphabet had ******* full-time workers in 2024.

The Quarterly Census of Employment and Wages (QCEW) program publishes a quarterly count of employment and wages reported by employers covering more than 95 percent of U.S. jobs, available at the county, MSA, state and national levels by industry. The dataset, hosted as part of the Cloud Public Datasets Program , gives county-level information on jobs and wages each quarter starting in 1990. The counties are identified by geoid which can easily be joined with both all FIPS codes or US county boundaries to unlock new insights within the data. Both of these datasets are available in BigQuery through the Cloud Public Datasets Cleaning and onboarding support for this dataset is provided by CARTO . This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

🔗 LinkedIn Job Postings Data - Comprehensive Professional Intelligence for HR Strategy & Market Research

LinkedIn Job Postings Data represents the most comprehensive professional intelligence dataset available, delivering structured insights across millions of LinkedIn job postings, LinkedIn job listings, and LinkedIn career opportunities. Canaria's enriched LinkedIn Job Postings Data transforms raw LinkedIn job market information into actionable business intelligence—normalized, deduplicated, and enhanced with AI-powered enrichment for deep workforce analytics, talent acquisition, and market research.

This premium LinkedIn job postings dataset is engineered to help HR professionals, recruiters, analysts, and business strategists answer mission-critical questions: • What LinkedIn job opportunities are available in target companies? • Which skills are trending in LinkedIn job postings across specific industries? • How are companies advertising their LinkedIn career opportunities? • What are the salary expectations across different LinkedIn job listings and regions?

With real-time updates and comprehensive LinkedIn job posting enrichment, our data provides unparalleled visibility into LinkedIn job market trends, hiring patterns, and workforce dynamics.

🧠 Use Cases: What This LinkedIn Job Postings Data Solves

Our dataset transforms LinkedIn job advertisements, market information, and career listings into structured, analyzable insights—powering everything from talent acquisition to competitive intelligence and job market research.

Talent Acquisition & LinkedIn Recruiting Intelligence • LinkedIn job market mapping • LinkedIn career opportunity intelligence • LinkedIn job posting competitive analysis • LinkedIn job skills gap identification

HR Strategy & Workforce Analytics • Organizational network analysis • Employee mobility tracking • Compensation benchmarking • Diversity & inclusion analytics • Workforce planning intelligence • Skills evolution monitoring

Market Research & Competitive Intelligence • Company growth analysis • Industry trend identification • Competitive talent mapping • Market entry intelligence • Partnership & business development • Investment due diligence

LinkedIn Job Market Research & Economic Analysis • Regional LinkedIn job analysis • LinkedIn job skills demand forecasting • LinkedIn job economic impact assessment • LinkedIn job education-industry alignment • LinkedIn remote job trend analysis • LinkedIn career development ROI

🌐 What Makes This LinkedIn Job Postings Data Unique

AI-Enhanced LinkedIn Job Intelligence • LinkedIn job posting enrichment with advanced NLP • LinkedIn job seniority classification • LinkedIn job industry expertise mapping • LinkedIn job career progression modeling

Comprehensive LinkedIn Job Market Intelligence • Real-time LinkedIn job postings with salary, requirements, and company insights • LinkedIn recruiting activity tracking • LinkedIn job application analytics • LinkedIn job skills demand analysis • LinkedIn compensation intelligence

Company & Organizational Intelligence • Company growth indicators • Cultural & values intelligence • Competitive positioning

LinkedIn Job Data Quality & Normalization • Advanced LinkedIn job deduplication • LinkedIn job skills taxonomy standardization • LinkedIn job geographic normalization • LinkedIn job company matching • LinkedIn job education standardization

🎯 Who Uses Canaria's LinkedIn Data

HR & Talent Acquisition Teams • Optimize recruiting pipelines • Benchmark compensation • Identify talent pools • Develop data-driven hiring strategies

Market Research & Intelligence Analysts • Track industry trends • Build competitive intelligence models • Analyze workforce dynamics

HR Technology & Analytics Platforms • Power recruiting tools and analytics solutions • Fuel compensation engines and dashboards

Academic & Economic Researchers • Study labor market dynamics • Analyze career mobility trends • Research professional development

Government & Policy Organizations • Evaluate workforce development programs • Monitor skills gaps • Inform economic initiatives

📌 Summary

Canaria's LinkedIn Job Postings Data delivers the most comprehensive LinkedIn job market intelligence available. It combines job posting insights, recruiting intelligence, and organizational data in one unified dataset. With AI-enhanced enrichment, real-time updates, and enterprise-grade data quality, it supports advanced HR analytics, talent acquisition, job market research, and competitive intelligence.

🏢 About Canaria Inc. Canaria Inc. is a leader in alternative data, specializing in job market intelligence, LinkedIn company data, Glassdoor salary analytics, and Google Maps location insights. We deliver clean, structured, and enriched datasets at scale using proprietary data scraping pipelines and advanced AI/LLM-based modeling, all backed by human validation. Our platform also includes Google Maps data, providing verified business locatio...

Traffic statistics for the For government franchise on the Queensland Government website. Source: Google Analytics.

📊 Job Postings Data for Talent Acquisition, HR Strategy & Market Research Canaria’s Job Postings Data product is a structured, AI-enriched dataset that captures and organizes millions of job listings from leading sources such as Indeed, LinkedIn, and other recruiting platforms. Designed for decision-makers in HR, strategy, and research, this data reveals workforce demand trends, employer activity, and hiring signals across the U.S. labor market and enhanced with advanced enrichment models.

The dataset enables clients to track who is hiring, what roles are being posted, which skills are in demand, where talent is needed geographically, and how compensation and employment structures evolve over time. With field-level normalization and deep enrichment, it transforms noisy job listings into high-resolution labor intelligence—optimized for strategic planning, analytics, and recruiting effectiveness.

🧠 Use Cases: What This Job Postings Data Solves This enriched dataset empowers users to analyze workforce activity, employer behavior, and hiring trends across sectors, geographies, and job categories.

🔍 Talent Acquisition & HR Strategy • Identify hiring trends by industry, company, function, and geography • Optimize job listings and outreach with enriched skill, title, and seniority data • Detect companies expanding or shifting their workforce focus • Monitor new roles and emerging skills in real time

📈 Labor Market Research & Workforce Planning • Visualize job market activity across cities, states, and ZIP codes • Analyze hiring velocity and job volume changes as macroeconomic signals • Correlate job demand with company size, sector, or compensation structure • Study occupational dynamics using AI-normalized job titles • Use directional signals (job increases/declines) to anticipate market shifts

📊 HR Analytics & Compensation Intelligence • Map salary ranges and benefits offerings by role, location, and level • Track high-demand or hard-to-fill positions for strategic workforce planning • Support compensation planning and headcount forecasting • Feed job title normalization and metadata into internal HRIS systems • Identify talent clusters and location-based hiring inefficiencies

🌐 What Makes This Job Postings Data Unique

🧠 AI-Based Enrichment at Scale • Extracted attributes include hard skills, soft skills, certifications, and education requirements • Modeled predictions for seniority level, employment type, and remote/on-site classification • Normalized job titles using an internal taxonomy of over 50,000 unique roles • Field-level tagging ensures structured, filterable, and clean outputs

💰 Salary Parsing & Compensation Insights • Parsed salary ranges directly from job descriptions • AI-based salary predictions for postings without explicit compensation • Compensation patterns available by job title, company, and location

🔁 Deduplication & Normalization • Achieves approximately 60% deduplication rate through semantic and metadata matching • Normalizes company names, job titles, location formats, and employment attributes • Ready-to-use, analysis-grade dataset—fully structured and cleansed

🔗 Company Matching & Metadata • Each job post is linked to a structured company profile, including metadata • Records are cross-referenced with LinkedIn and Google Maps to validate company identity and geography • Enables aggregation at employer or location level for deeper insights

🕒 Freshness & Scalability • Updated hourly to reflect real-time hiring behavior and job market shifts • Delivered in flexible formats (CSV, JSON, or data feed) and customizable filters • Supports segmentation by geography, company, seniority, salary, title, and more

🎯 Who Uses Canaria’s Job Postings Data • HR & Talent Teams – to benchmark roles, optimize pipelines, and compete for talent • Consultants & Strategy Teams – to guide clients with labor-driven insights • Market Researchers – to understand employment dynamics and job creation trends • HR Tech & SaaS Platforms – to power salary tools, job market dashboards, or recruiting features • Economic Analysts & Think Tanks – to model labor activity and hiring-based economic trends • BI & Analytics Teams – to build dashboards that track demand, skill shifts, and geographic patterns

📌 Summary Canaria’s Job Postings Data provides an AI-enriched, clean, and analysis-ready view of the U.S. job market. Covering millions of listings from Indeed, LinkedIn, other job boards, and ATS sources, it includes detailed job attributes, inferred compensation, normalized titles, skill extraction, and employer metadata—all updated hourly and fully structured.

With deep enrichment, reliable deduplication, and company matchability, this dataset is purpose-built for users needing workforce insights, market trends, and strategic talent intelligence. Whether you're modeling skill gaps, benchmarking compensation, or visualizing hiring momentum, this dataset provides a complete toolkit for HR and labor intellig...

Being a centre of academic pursuits and intellectual rigour, universities frequently place a high demand on the psychological and emotional well-being of their workers. This study aims to explore the relationship between perceived stress, anxiety, and depression among employees in a university in Nigeria and explore how these stress levels are associated with anxiety and depression. We conducted a cross-sectional study in a foremost private university in Southwestern Nigeria between 28th January 2024 and 11th April 2024. The participants completed a set of self-report questionnaires measuring perceived stress, anxiety and depression symptoms, and demographic information via an electronic survey platform (Google Forms). Data was analyzed using descriptive and inferential statistics. The results showed that both perceived stress (r = 0.517, p = 0.01) and family history of heart attack (p = 0.026) were found to be significantly associated with depression (p = 0.05). The logistic regression analysis revealed that, even after adjusting for hypertension (OR = 10.43, 95% CI = 1.761–61.799), high perceived stress remained significantly associated with both anxiety (OR, 95% confidence interval (CI) = 1.761–61.799; p = .010) and depression (OR, 42.91; 95%CI = 7.557–243.605) compared with those who experienced either moderate or low levels of stress. The study showed that perceived stress is associated with anxiety and depression. Findings are expected to inform policymakers and university administrators, guiding the implementation of effective mental health support systems and stress management interventions within Nigerian universities.

Prevalence of perceived stress, anxiety, and depression among the participants (n = 275).

Employee engagement in the world increased from 2011 to 2020, but dropped slightly the next years. It stood at ** percent in 2022 and 2023. It was at its highest in 2020 when it reached ** percent.

Correlation and mean/standard deviation for all variables (n = 275).

The tech industry had a rough start to 2024. Technology companies worldwide saw a significant reduction in their workforce in the first quarter of 2024, with over 57 thousand employees being laid off. By the second quarter, layoffs impacted more than 43 thousand tech employees. In the final quarter of the year around 12 thousand employees were laid off. Layoffs impacting all global tech giants Layoffs in the global market escalated dramatically in the first quarter of 2023, when the sector saw a staggering record high of 167.6 thousand employees losing their jobs. Major tech giants such as Google, Microsoft, Meta, and IBM all contributed to this figure during this quarter. Amazon, in particular, conducted the most rounds of layoffs with the highest number of employees laid off among global tech giants. Industries most affected include the consumer, hardware, food, and healthcare sectors. Notable companies that have laid off a significant number of staff include Flink, Booking.com, Uber, PayPal, LinkedIn, and Peloton, among others. Overhiring led the trend, but will AI keep it going? Layoffs in the technology sector started following an overhiring spree during the COVID-19 pandemic. Initially, companies expanded their workforce to meet increased demand for digital services during lockdowns. However, as lockdowns ended, economic uncertainties persisted and companies reevaluated their strategies, layoffs became inevitable, resulting in a record number of 263 thousand laid off employees in the global tech sector by trhe end of 2022. Moreover, it is still unclear how advancements in artificial intelligence (AI) will impact layoff trends in the tech sector. AI-driven automation can replace manual tasks leading to workforce redundancies. Whether through chatbots handling customer inquiries or predictive algorithms optimizing supply chains, the pursuit of efficiency and cost savings may result in more tech industry layoffs in the future.

BackgroundHomelessness staff often experience high job demands, limited resources, and significant emotional strains; with high levels of burnout, stress, and trauma being common within the workforce. Despite growing recognition of these issues, limited literature exists on interventions to address them. This study aims to conduct a systematic scoping review to map and identify interventions aimed at improving well-being and reducing burnout among homelessness staff.MethodsAll eligible studies needed to include an intervention addressing burnout and/or well-being in homelessness staff, published in English with primary data. Evidence sources were left open with no data restrictions. Following protocol registration, a systematic search of five electronic databases (Medline, APA PsychInfo, Global Health, ASSIA, CINAHL) and Google Scholar was conducted. Studies were double-screened for inclusion. Methodological quality was assessed using the Mixed Methods Appraisal Tool.ResultsOf the 5,775 screened studies, six met the inclusion criteria: two peer-reviewed and four non-peer-reviewed publications. No studies were retrieved from Google Scholar. The included studies comprised four quantitative non-randomised designs, one randomised controlled trial, and one mixed-methods study. All included studies were complex interventions. Three were therapy-based, two included supervision, and two were one-time educational sessions. Most were conducted in the United States (n = 4), with two in the United Kingdom. The total pooled sample was 347 participants, though four studies were missing demographic data (age and gender). The studies used heterogenous measures and outcomes. Limitations included restrictions to English-only publications, potential gaps in capturing well-being measures, and a limited grey literature scope.ConclusionThere is a lack of research on well-being and burnout interventions in frontline homelessness staff. Identified studies were generally low quality, using heterogenous measures and outcomes to assess well-being and burnout, limiting the generalisability of findings. Future research should employ more robust study designs with standardised measures and outcomes.