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.
Companies with the most open Google BigQuery roles
25 of 674 · the full list is in the API| Company | Size | Open roles | Teams hiring | Median stated pay |
|---|---|---|---|---|
| 1001-5000 | 38 | Solutions engineering, Product management, Backend engineering | $207k | |
| 5000+ | 29 | Solutions engineering, Enterprise applications, AI and machine learning | $186k | |
| 11-50 | 26 | Backend engineering, Engineering leadership, Finance | $256k | |
| 5000+ | 21 | Backend engineering, Data science, Analytics | $145k | |
| 1001-5000 | 21 | Data science, Analytics | $69k | |
| 5000+ | 20 | Data science, Analytics, AI and machine learning | $131k | |
| 1001-5000 | 18 | Backend engineering, AI and machine learning, Frontend engineering | $231k | |
| 5000+ | 17 | Analytics, Data science, Sales | — | |
| 16 | Data science, Backend engineering, DevOps and infrastructure | — | ||
| 16 | Data science | $145k | ||
| 5000+ | 15 | Analytics, Data science, AI and machine learning | — | |
| 1001-5000 | 13 | Customer success, Solutions engineering, Engineering leadership | $158k | |
| 51-200 | 12 | Solutions engineering, Engineering leadership, Product management | — | |
| 501-1000 | 12 | Enterprise applications, Data science, Marketing | $132k | |
| 1001-5000 | 10 | Engineering leadership, Data science, Backend engineering | $383k | |
| 1001-5000 | 10 | Security, Enterprise applications | $87k | |
| 501-1000 | 10 | Data science, Solutions engineering, AI and machine learning | — | |
| 5000+ | 10 | Analytics, Backend engineering, Product management | $114k | |
| 5000+ | 10 | Data science, AI and machine learning, DevOps and infrastructure | $148k | |
| 5000+ | 10 | DevOps and infrastructure, Data science, Engineering leadership | $99k | |
| 1001-5000 | 10 | Analytics, Product management | — | |
| 201-500 | 9 | Backend engineering, Data science, Enterprise applications | $205k | |
| 5000+ | 9 | Data science, Engineering leadership, AI and machine learning | $195k | |
| 1001-5000 | 8 | Solutions engineering, Data science, QA and testing | $90k | |
| 501-1000 | 8 | Solutions engineering, Product management, Backend engineering | $260k |
Google BigQuery in other countries
What these companies also use
Teams hiring for Google BigQuery
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.
