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Remote Google Bigquery Jobs (NOW HIRING)

Ripple Effect Strategies

Data Associate - UI

$80K/yr

Data Associate - UI Location: Remote Salary: $80,000/year (Full-Time) About Ripple Effect ... Data platforms such as Google BigQuery * Programming languages such as C++ * Startup environments ...

PTP

Google Cloud Solution Architect - REMOTE

Austin, TX · Remote

$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 ...

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

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 ...

phData

Solutions Architect

OR · On-site +1

$63 - $83/hr

Snowflake, Databricks, Google BigQuery, AWS, Microsoft Azure, Google Cloud Platform. * Hands-on ... Remote-First Work Environment * 401k plan with company match * Dental and Vision insurance * Home ...

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How much do remote google bigquery jobs pay per hour?

As of Sep 2, 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 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.

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 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.

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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 77% Full Time, 8% Part Time, and 15% Contract. Highlights an 100% Remote job distribution, with an average salary of $57,562 per year, or $27.7 per hour.

EPBCS Integration Specialist (Remote)

Delan Associates, Inc

Jersey City, NJ • Remote

Full-time

Re-posted 5 days ago

Job description

Job Description:

Project : EPBCS to Data Lake Integration

Role Summary: We are seeking an experienced EPBCS Integration Specialist to design, develop, and support the integration of Oracle Enterprise Planning and Budgeting Cloud Service (EPBCS) with enterprise Data Lake platforms. The ideal candidate will have strong expertise in Oracle EPM technologies, data integration, SQL, ETL development, and data quality management.

Experience Required:

5+ years of experience with Oracle EPBCS / Planning Cloud

3+ years of experience in EPBCS data integration projects

2+ years of experience working with Data Warehouse platforms such as Snowflake, Google BigQuery, or Azure Synapse

Required Skills:

Strong experience with Oracle EPBCS, including:

Metadata

Dimensions

Actuals

Budgets

APIs

Strong SQL development skills

ETL tools experience such as:

Informatica

Talend

Apache Airflow

Experience with data quality validation and data reconciliation

Key Responsibilities

Design the EPBCS extraction and Data Lake integration strategy.

Develop dimension, actuals, and budget data pipelines.

Implement data validation and reconciliation processes.

Optimize integration performance and troubleshoot production issues.

Develop technical documentation and operational runbooks.

Best Practices

Data Architecture

Versioned dimensions

Incremental actuals loads

Budget versioning

Maintain lineage and metadata

Data Quality

Pre-load and post-load validation

Reconciliation checks

Row count verification

Data consistency validation

Integration Patterns

Full dimension extracts

Incremental actuals extraction

Budget version management

Performance

Batch exports

Parallel extraction

Bulk data loading

Partitioning

Data compression

Deliverables

Integration architecture and data flow design

Data mapping specifications

Version-controlled ETL/ELT pipelines

Data quality validation framework

Reconciliation reports

Operational runbooks