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Remote Google Bigquery Jobs (NOW HIRING)

Argano

Senior Pigment Consultant (Remote)

Minneapolis, MN · Remote

$95K - $130K/yr

... Google BigQuery, S3, etc.) * Knowledge of Excel, SQL, programming logic What We Offer * Flexible ... Remote work flexibility * Trendy, collaborative and dog-friendly office at our HQ in Minneapolis ...

Ruri Software Technologies LLC

Druid Architect

Remote Duration : 8+ months Primary Skills : GitLab, Linux, Apache Druid, Google Compute Engine, Google Cloud Platform, BigQuery, Apache Airflow * Secondary Skills : Python, Shell Script, Pyspark

PTP

Google Cloud Solution Architect - REMOTE

Austin, TX · On-site +1

$62 - $84.75/hr

Dialogflow CX/ES, Conversational Insights, Speech to Text, BigQuery, Pub/Sub, GKE or Cloud Run, and/or Vertex AI • Expert in Google Cloud foundational best practices for IAM, project hierarchy ...

Flip To, Inc.

Senior Full-stack Engineer (Remote)

Maitland, FL · Remote

$113K - $150K/yr

Azure SQL, GA 360 & Google BigQuery * C#, ASP.Net & Angular * Several other cloud services used to analyze the immense amount of data that we collect, as well as to increase our platform performance ...

Hikinex

REMOTE OR HYBRID IS POSSIBLE FOR THE RIGHT CANDIDATE. Open for candidates in Canada as well as the ... Google BigQuery). • Familiarity with containerized database deployment (Docker, Kubernetes)

SWITS DIGITAL Private Limited

Data Engineer - GCP

$117K - $140K/yr

Denver, CO (Remote) Job Summary The client is seeking a highly skilled Data Engineer with deep ... Strong hands-on experience with Google Cloud Platform (GCP) * Expertise in BigQuery (partitioning ...

Kohl's

Experience with Google BigQuery Essential Functions The requirements listed below are representative of functions you will be required to perform, however you may be required to perform additional ...

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How much do remote google bigquery jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for remote google bigquery in the United States is $27.67, according to ZipRecruiter salary data. Most workers in this role earn between $21.63 and $33.17 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals working remotely with Google BigQuery, and how can they be addressed?

One common challenge remote Google BigQuery professionals face is optimizing query performance while managing cost, since inefficient queries can quickly increase expenses. Collaboration with distributed teams can also be tricky, especially when aligning on data schema changes or troubleshooting issues across time zones. To address these, it's helpful to establish clear documentation practices, use version control for SQL scripts, and schedule regular check-ins with team members. Leveraging Google BigQuery's built-in monitoring and cost control tools also helps maintain project efficiency and budget constraints.

What is the difference between Remote Google Bigquery vs Remote Data Analyst?

AspectRemote Google BigqueryRemote Data Analyst
Required CredentialsSQL, Cloud certifications, Google Cloud certificationsSQL, Data analysis, Excel, sometimes certifications
Work EnvironmentCloud platforms, data warehouses, remote teamsData visualization tools, spreadsheets, reporting platforms
Industry UsageData engineering, cloud services, analyticsBusiness intelligence, reporting, insights

Remote Google Bigquery specialists focus on managing and querying large datasets using Google Cloud, requiring technical skills and cloud certifications. Remote Data Analysts interpret data, create reports, and provide insights, often using visualization tools. While both roles work remotely and handle data, Bigquery roles are more technical and cloud-focused, whereas Data Analysts focus on analysis and reporting.

What are the key skills and qualifications needed to thrive as a remote Google BigQuery specialist?

To excel as a Remote Google BigQuery Specialist, you need a solid background in SQL, data warehousing concepts, and experience with cloud-based analytics platforms, typically supported by a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP), BigQuery ML, data visualization tools like Looker or Tableau, and relevant certifications such as Google Professional Data Engineer are highly beneficial. Strong problem-solving skills, attention to detail, and effective remote communication set top performers apart. These skills and qualifications enable efficient management of large datasets, insightful analytics, and seamless collaboration in distributed teams.

What is a remote Google BigQuery?

A Remote Google BigQuery job is a position where professionals manage, analyze, and optimize large datasets using Google BigQuery, a fully-managed cloud data warehouse, while working from a location outside of a traditional office. These roles typically involve writing SQL queries, building data pipelines, and collaborating with data engineers and analysts to derive insights from data stored in the cloud. Remote BigQuery specialists may also be responsible for maintaining data security, optimizing query performance, and integrating BigQuery with other data tools. This flexible setup allows employees to work from anywhere with a stable internet connection while supporting organizations' data needs.
More about Remote Google Bigquery jobs
What cities are hiring for Remote Google Bigquery jobs? Cities with the most Remote Google Bigquery job openings:
What are the most commonly searched types of Google Bigquery jobs? The most popular types of Google Bigquery jobs are:
What states have the most Remote Google Bigquery jobs? States with the most job openings for Remote Google Bigquery jobs include:
What job categories do people searching Remote Google Bigquery jobs look for? The top searched job categories for Remote Google Bigquery jobs are:
Remote Google Bigquery jobs near you
Infographic showing various Remote Google Bigquery job openings in the United States as of August 2026, with employment types broken down into 57% Full Time, and 43% Contract. Highlights an 100% Remote job distribution, with an average salary of $57,562 per year, or $27.7 per hour.

Looker BI Analyst (100% Remote)

Pddn

San Francisco, CA • Remote

Contractor

Re-posted 27 days ago

Job description

Job Description:

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Must have 5+ years of experience with implementing and managing BI platforms for business intelligence, data applications, and embedded analytics.

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Experience with Looker a cloud-based business intelligence (BI) platform designed to explore and analyze data.

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Must have 2 years of experience in developing LOOKML, Looker Dashboards and Look-Linked Tiles.

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Must have strong expertise in SQL, preferably across multiple dialects.

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Build, maintain and administer Looker as the primary BI tool and be the driving force behind the adoption and effective use of Looker within every team.

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Must be a Data Explorer using Looker daily to create and curate content, as well as prior experience with data visualization and building reports.

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Experience with Looker Explores to query data, validate data accuracy, identify error sources and control content access for security.

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Experience in Data visualizations, Scheduling and sharing Looks and dashboards, Table calculations, Looker expressions, Custom and advanced filters, Impacts of pivoting.

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Experience with best practices around designing dashboards, Fundamentals of caching and reporting tools: Tableau, Excel, Power BI, etc.

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Maintain and debug LookML code, Build user-friendly Explores, Design robust models, Define caching policies, Understand various datasets and associated schemas.

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Experience with Looker IDE, Text editor, Looker's SQL Runner, Content Validator, LookML Validator and Version control.

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Troubleshoot errors in existing data models. Implement data security requirements. Analyze data models and business requirements to create LookML objects.

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Design new LookML dimensions and Build Explores for users to answer business questions and optimize queries and reports for performance.

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Implement persistent derived tables, caching policies, version control and assess code quality, utilize SQL Runner for data validation.

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Experience with Looker query builder, Looker SQL generator, LookML models and views.

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Knowledge with a scripting language (Python, Ruby, etc.) to build data models and ETL workflow modeling.

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Knowledge of relational Databases or Data Warehouses (Amazon Redshift, Google BigQuery, PostgreSQL, MySQL, Snowflake, etc.)

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