Companies in the United States using Google BigQuery

674 companies headquartered in the United States list Google BigQuery as a requirement in 1,544 open roles. Most of those roles are in data science, analytics and backend engineering teams. Google BigQuery most often appears next to BigQuery, Python, SQL, GCP and AWS. Roles that need it and state the pay sit at $170k a year in the middle.

From the requirements of live job postingsRebuilt 8 Oct 2026
companies hiring
674
open roles need it
1,544
median stated pay
$170k

Companies with the most open Google BigQuery roles

25 of 674 · the full list is in the API
CompanySizeOpen rolesTeams hiringMedian stated pay
Fivetran1001-500038Solutions engineering, Product management, Backend engineering$207k
Salesforce5000+29Solutions engineering, Enterprise applications, AI and machine learning$186k
Félix Pago11-5026Backend engineering, Engineering leadership, Finance$256k
Walmart5000+21Backend engineering, Data science, Analytics$145k
Air Apps1001-500021Data science, Analytics$69k
Mattel5000+20Data science, Analytics, AI and machine learning$131k
Reddit1001-500018Backend engineering, AI and machine learning, Frontend engineering$231k
WPP Media5000+17Analytics, Data science, Sales—
DoiT16Data science, Backend engineering, DevOps and infrastructure—
CapTech16Data science$145k
General Mills5000+15Analytics, Data science, AI and machine learning—
Sigma Computing1001-500013Customer success, Solutions engineering, Engineering leadership$158k
Hevo Data51-20012Solutions engineering, Engineering leadership, Product management—
Formlabs501-100012Enterprise applications, Data science, Marketing$132k
Anthropic1001-500010Engineering leadership, Data science, Backend engineering$383k
Mozilla Corporation1001-500010Security, Enterprise applications$87k
Tiger Analytics501-100010Data science, Solutions engineering, AI and machine learning—
TransUnion5000+10Analytics, Backend engineering, Product management$114k
Accenture Federal Services5000+10Data science, AI and machine learning, DevOps and infrastructure$148k
Omnicom5000+10DevOps and infrastructure, Data science, Engineering leadership$99k
Las Vegas Convention and Visitors Authority1001-500010Analytics, Product management—
TRM Labs201-5009Backend engineering, Data science, Enterprise applications$205k
Citi5000+9Data science, Engineering leadership, AI and machine learning$195k
Bloomreach1001-50008Solutions engineering, Data science, QA and testing$90k
ClickHouse501-10008Solutions engineering, Product management, Backend engineering$260k

Google BigQuery in other countries

Teams hiring for Google BigQuery

Data science475
Analytics232
Backend engineering208
Solutions engineering109
AI and machine learning97
DevOps and infrastructure80
Engineering leadership80
Product management44

Get all 674 companies as a list

Name, website, size, industry and headquarters of every company that requires Google BigQuery, through the API (company.getList with technology=Google BigQuery and country=US). 674 companies × 0.02 credits = 13.48 credits ($1.35).

Questions

How do you know a company uses Google BigQuery?

A company counts when at least one of its open job postings lists Google BigQuery as a requirement, not as a nice-to-have. The list is rebuilt every night from the postings on the employers' own careers boards. Staffing agencies, job republishers and the maker of Google BigQuery itself are left out.

Which teams hire for Google BigQuery?

Of the 1,544 open roles that require it, most are in data science (475), analytics (232) and backend engineering (208).

What do Google BigQuery roles pay?

707 of the 1,544 roles state the pay. The middle of their posted ranges is $170k a year, converted to US dollars.

Can I download this list?

Yes, through the API: company.getList with technology=Google BigQuery and country=US returns each company's name, website, size, industry and headquarters for 0.02 credits a row (a credit is $0.10). New accounts start with 30 free credits.

Source: the requirements of 1,544 live job postings on employers' careers boardsUpdated 8 Oct 2026MethodologyJSONCC BY-SA 4.0