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Google Bigquery Jobs in California (NOW HIRING)

Google

Software Engineer III, BigQuery ML

Sunnyvale, CA · On-site

$134K - $161K/yr

Experience with Google Cloud Platform (GCP) services especially Data Analytics Services and Vertex ... Data Analytics, BigQuery, Evaluations, Statistical Analysis, Inference. About the job Google ...

Extractable

Python Integrations Developer

San Francisco, CA · Remote

$59.25 - $81.50/hr

Google Analytics 4, Google BigQuery, Google Tag Manager, Looker Requirements Must Have * 3+ years experience building and maintaining third-party API integrations - REST, SOAP, webhooks, file-based ...

Extractable

Python Integrations Developer

San Francisco, CA · On-site

$100K - $130K/yr

Google Analytics 4, Google BigQuery, Google Tag Manager, Looker Requirements Must Have * 3+ years experience building and maintaining third-party API integrations - REST, SOAP, webhooks, file-based ...

Extractable

Python Integrations Developer

San Francisco, CA · Remote

$59.25 - $81.50/hr

Google Analytics 4, Google BigQuery, Google Tag Manager, Looker Requirements Must Have * 3+ years experience building and maintaining third-party API integrations - REST, SOAP, webhooks, file-based ...

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All JobsGoogle Bigquery JobsGoogle Bigquery Jobs in California

Google Bigquery information

See California salary details

$24.5K

$109.1K

$175.3K

How much do google bigquery jobs pay per year?

As of Aug 19, 2026, the average yearly pay for google bigquery in California is $109,126.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,077.00 and $146,884.00 per year, depending on experience, location, and employer.

What is a Google BigQuery?

A Google BigQuery job is an asynchronous task used to run queries, load data, export data, or copy data within BigQuery. Each job is assigned a unique job ID and executes in the background, meaning it doesn't require continuous user interaction. There are different types of jobs: query jobs for running SQL queries, load jobs for importing data, export jobs for extracting data, and copy jobs for duplicating tables. Jobs can be managed and monitored through the BigQuery UI, CLI, or API.

What are the key skills and qualifications needed to thrive in the Google BigQuery position?

To excel in a Google BigQuery role, proficiency in SQL, data warehousing concepts, and cloud architecture is essential, often supported by a relevant degree in computer science or data analytics. Familiarity with the Google Cloud Platform (GCP), BigQuery-specific tools, and related certifications like Google Professional Data Engineer are highly valued. Strong analytical thinking, attention to detail, and effective communication skills help professionals distill complex data sets and collaborate across teams. These competencies are vital for efficiently managing, analyzing, and leveraging large-scale data within organizations to drive actionable business insights.

What are some typical projects or challenges faced by professionals working with Google BigQuery?

Professionals working with Google BigQuery often tackle projects involving the integration, analysis, and visualization of massive data sets to support business decision-making. Common challenges include optimizing query performance, managing data security and governance, and designing scalable data pipelines to handle rapidly growing information. Day-to-day, you might collaborate with data engineers, data analysts, and business stakeholders to interpret results and translate findings into actionable strategies. This role offers the opportunity to stay at the forefront of cloud data technologies while making a measurable impact on organizational goals.

Is Google Bigquery hard to learn?

Google BigQuery is a cloud-based data warehouse that requires understanding SQL and data analysis concepts. While it has a learning curve for beginners, many resources and tutorials are available to help new users become proficient quickly, especially if they have prior experience with SQL or data management tools.

What are jobs in Google Bigquery?

Jobs related to Google BigQuery typically involve managing, analyzing, and optimizing large datasets using SQL and cloud-based tools. Common roles include data analysts, data engineers, and database administrators who require knowledge of BigQuery, cloud computing, and data warehousing concepts. These positions often demand familiarity with Google Cloud Platform and related certifications.

What is Google BigQuery used for?

Google BigQuery is a cloud-based data warehouse used for storing and analyzing large datasets quickly and efficiently. It enables data analysts and data engineers to run complex SQL queries, perform data analytics, and generate insights from big data without managing infrastructure. Skills in SQL and cloud environments are essential for working effectively with BigQuery.

What are the most commonly searched types of Google Bigquery jobs in California?

The most popular types of Google Bigquery jobs in California are:

What are popular job titles related to Google Bigquery jobs in California?

For Google Bigquery jobs in California, the most frequently searched job titles are:

What job categories do people searching Google Bigquery jobs in California look for?

The top searched job categories for Google Bigquery jobs in California are:

What cities in California are hiring for Google Bigquery jobs?

Cities in California with the most Google Bigquery job openings:

Google Bigquery jobs near you
Infographic showing various Google Bigquery job openings in California as of August 2026, with employment types broken down into 89% Full Time, 7% Part Time, and 4% Contract. Highlights an 68% Physical, 4% Hybrid, and 28% Remote job distribution, with an average salary of $109,126 per year, or $52.5 per hour.

Looker + Google BigQuery Architect

Apetan Consulting llc

San Ramon, CA • On-site

Contractor

Posted 12 days ago

Job description

Position - Looker + Google BigQuery Architect
Location: San Ramon, California, USA
Work Mode: 5 days WFO
Experience: 10–14 years (minimum 4–5 years in Looker & GCP Data Stack)
About the Role
We are looking for an experienced Looker + GBQ Architect to lead analytics solutioning, architecture design, and performance optimization across our enterprise-scale data ecosystem. The ideal candidate should have a strong foundation in data modeling, LookML, and GCP (BigQuery, Cloud Composer, Dataflow, Pub/Sub) with the ability to work directly with business stakeholders, data engineers, and visualization teams.
This role will anchor our BI modernization journey for Data Engineering AMS and Looker Functional teams, ensuring scalable, secure, and performant data analytics delivery.
 

Key Responsibilities
1. Solution Architecture & Design
• Design and implement end-to-end Looker + GBQ architecture, ensuring scalability and alignment with enterprise data strategy.
• Define semantic layer, LookML models, and reusable data components for cross-functional BI use cases.
• Create and enforce best practices for data modeling, partitioning, and optimization in BigQuery.
2. Development & Implementation
• Lead Looker dashboard and data model development for business-critical functions (Finance, Sales, Product).
• Collaborate with DE & BI teams to define data pipelines feeding Looker, ensuring freshness, lineage, and consistency.
• Enable parameterized and governed exploration within Looker for end-users and analysts.
3. Governance, Security & Performance
• Implement row-level and column-level security models in Looker and GBQ.
• Optimize query performance and cost management within GBQ.
• Drive monitoring, logging, and SLA adherence for Looker reports and data sources.
• Establish automated health checks and observability dashboards across BI environments.
4. Collaboration & Leadership
• Work closely with product owners, business analysts, and DE teams to translate business KPIs into scalable data models.
• Mentor and guide the Looker Functional Team and ensure alignment with global data architecture standards.
• Contribute to the data governance framework, ensuring compliance with enterprise and regulatory guidelines.
5. Continuous Improvement & Innovation
• Evaluate and integrate AI/ML and advanced analytics within Looker/GBQ ecosystem where applicable.
• Identify opportunities to automate operational reporting and ticket workflows (e.g., integration with Wolken or JIRA).
• Drive adoption of modern Looker features (Looker Blocks, Looker API, embedded analytics).
Required Skills
• Strong proficiency in:
• Looker, LookML, and Looker API
• Google BigQuery, Dataform / dbt, Cloud Composer, Pub/Sub
• SQL optimization and cost-efficient query structuring
• Experience with:
• Building scalable semantic models and data marts
• Implementing BI and data access governance
• Cross-functional collaboration with Data Engineering and Cloud Ops
• Soft Skills: Excellent communication, stakeholder management, mentoring, and problem-solving ability.
Preferred Qualifications
• Looker Certification (LookML Developer / Looker Business Analyst)
• Google Cloud Professional Data Engineer / Architect certification
• Experience in AMS / Managed Service environment or data product operations.
• Exposure to Snowflake / dbt migration to GBQ is a plus.