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Remote Gcp Data Engineer Jobs in Berkeley, CA (NOW HIRING)

Data Engineer

Emeryville, CA · Remote

$132K - $159K/yr

TITLE: DATA ENGINEER LOCATION: 100% remote Skillsets/experience: * Engineer background * Google Applications/Analytics experience required * Google Search console experience required * Google Tag ...

Data Engineer

San Francisco, CA · On-site +1

$145K/yr

This is a remote position. Duties * Support production systems and help triage issues during live ... Department Data Engineering Locations San Francisco, CA - Remote Remote status Fully Remote

Data Engineer

San Francisco, CA · On-site +1

$160K/yr

This is a remote position. Duties * Support production systems and help triage issues during live ... Department Data Engineering Locations San Francisco, CA - Remote Remote status Fully Remote

Data Engineer

San Francisco, CA · Remote

$134K - $162K/yr

We're ready to welcome Slite's first data engineer ... This is a remote position. What's my mission ? Own the BItoolchain : pick, implement and maintain ...

Data Engineer

San Francisco, CA · Remote

$134K - $162K/yr

We're ready to welcome Slite's first data engineer ... This is a remote position. What's my mission ? Own the BItoolchain : pick, implement and maintain ...

The Swish Analytics team is seeking Data Engineers based in Europe to have a direct impact on the ... This is a remote position. Duties * Support production systems and help triage issues during live ...

The Swish Analytics team is seeking Data Engineers to have a direct impact on the infrastructure ... This is a remote position. Duties * Support production systems and help triage issues during live ...

Lead Data Engineer

Alameda, CA · Remote

$155K - $175K/yr

... data engineering products; lean into DataOps, DevOps, and CI/CD to deliver reliable, tested, and ... This is a fully remote position, with responsibilities that require strong communication skills and ...

Be Seen First

GCP cloud experience, including BigQuery and other cloud-native services * Experience working with ... Background in AI Engineering, Software Engineering, Machine Learning Engineering, or Data ...

New

Senior Data Engineer

San Francisco, CA · On-site +1

$124K - $169K/yr

Learn more in our CEO's funding announcement: We're a small, remote-first team. We take ownership ... We practice software engineering for data . Pipelines are code with tests, CI/CD, and ...

Software Engineer, Data Engineering

San Francisco, CA · On-site +1

$134K - $162K/yr

United States (remote) What is Verse? The race to AI has become the race to power. Every ... Experience building event-driven architectures with streaming tools such as Kafka, NATS, GCP Pub ...

The role We're looking for a Senior Data Engineer to help the team deliver data science services ... We are a remote-first company for most positions so you may work from anywhere you like in the U.S ...

Databricks Architect

Pleasanton, CA · Remote

$72 - $94.50/hr

Remote 10+ years experience in data eng, data platforms & analytics, 10+ years of consulting ... Engineering Professional certification & required classes Hands-on experience in development on ...

Databricks Architect

Pleasanton, CA · On-site +1

$72 - $94.50/hr

Remote • 10+ years experience in data eng, data platforms & analytics, 10+ years of consulting ... Data Engineering Professional certification & required classes • Hands-on experience in ...

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Showing results 1-20

Remote Gcp Data Engineer information

See Berkeley, CA salary details

$54.5K

$158.8K

$217.3K

How much do remote gcp data engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote gcp data engineer in Berkeley, CA is $158,830.00, according to ZipRecruiter salary data. Most workers in this role earn between $140,200.00 and $168,400.00 per year, depending on experience, location, and employer.

What is a remote GCP data engineer?

A Remote GCP Data Engineer is a technology professional who designs, builds, and manages data solutions using Google Cloud Platform (GCP), working from a remote location rather than an office. Their responsibilities include developing data pipelines, optimizing data storage, and ensuring efficient data processing on GCP services like BigQuery, Dataflow, and Cloud Storage. They collaborate with data scientists, analysts, and other engineers to support an organization's data needs while leveraging the flexibility of remote work.

How does a remote GCP data engineer typically collaborate with cross-functional teams when working offsite?

As a Remote GCP Data Engineer, you will frequently collaborate with data scientists, analysts, and product teams using virtual tools such as Slack, Jira, and Google Meet. Regular stand-ups and sprint planning meetings ensure alignment on project goals and timelines. Clear documentation and version control (often via Git) are crucial for smooth handoffs and code reviews, while cloud-based development environments streamline collaborative problem-solving. Successful remote collaboration relies on proactive communication and a willingness to adapt to various team workflows.

What are the key skills and qualifications needed to thrive as a remote GCP data engineer, and why are they important?

To thrive as a Remote GCP Data Engineer, you need expertise in data engineering concepts, SQL, Python, and a solid understanding of cloud computing, especially Google Cloud Platform (GCP) services like BigQuery and Dataflow, often supported by a relevant degree or GCP certification. Familiarity with tools such as Cloud Storage, Pub/Sub, Dataform, and workflow orchestration systems is typically required. Strong problem-solving, communication, and self-management skills set top candidates apart in remote environments. These abilities ensure efficient data processing, seamless collaboration, and successful delivery of scalable cloud-based solutions.

What is the difference between Remote Gcp Data Engineer vs Remote Data Analyst?

AspectRemote Gcp Data EngineerRemote Data Analyst
Required CredentialsGCP certifications, SQL, Python, data engineering skillsData analysis certifications, SQL, Excel, visualization tools
Work EnvironmentCloud platforms, data pipelines, infrastructure managementData interpretation, reporting, visualization
Employer & Industry UsageTech, finance, healthcare companies using cloud data solutionsMarketing, business intelligence, research firms

Remote Gcp Data Engineers focus on building and maintaining data pipelines on Google Cloud Platform, requiring cloud and engineering skills. Remote Data Analysts interpret data and create reports, often using visualization tools. While both roles require SQL and data handling, Gcp Data Engineers are more technical and infrastructure-oriented, whereas Data Analysts focus on insights and presentation.

What are popular job titles related to Remote Gcp Data Engineer jobs in Berkeley, CA?

For Remote Gcp Data Engineer jobs in Berkeley, CA, the most frequently searched job titles are:

What job categories do people searching Remote Gcp Data Engineer jobs in Berkeley, CA look for?

The top searched job categories for Remote Gcp Data Engineer jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Remote Gcp Data Engineer jobs?

Cities near Berkeley, CA with the most Remote Gcp Data Engineer job openings:

Infographic showing various Remote Gcp Data Engineer job openings in Berkeley, CA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $158,830 per year, or $76.4 per hour.

AI Data Engineer - Scientific Data Platforms (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$35 - $38/hr

Full-time

Re-posted 22 days ago


Job description

Pay Rate Low: 35 | Pay Rate High: 40
Our client is a leading global biotechnology and pharmaceutical organization driven by a mission to innovate, continuously advance science, and ensure everyone has access to the healthcare they need.
Title: AI Data Engineer - Scientific Data Platforms
Location: Remote, Must work PST
Pay rate: $35-38/hr (Depends on experience level)
Schedule: Full-time (40 hours/week)
Duration: 1-year contract, (Plus benefits)
Position Overview
This role addresses a critical need in scaling our AI models for drug discovery by building largely automated, scalable, agent-driven data ingestion and curation pipelines for genomics data. This includes metadata inference, constructing performant query architectures, and transforming high-dimensional datasets (e.g., single-cell omics, clinical trials) into AI-ready training formats.
Key Responsibilities
  • Build an agentic data ingestion pipeline and move beyond bespoke steps toward agents that teams can reliably use as a shared, deployed service.
  • Triage and prioritize incoming requests to ingest specific datasets. Clean and organize data, building the first-pass cleaning and organization steps into the agentic flow.
  • Validate cross-modal linkage. Add automated checks that catch when ingested data does not connect correctly and flag low-quality or mismatched records.
  • Version every dataset, retaining and making prior versions addressable. Preserve raw data and provenance, ensuring agent workflows log validation and transformation steps so lineage is fully traceable.
  • Partner with AI, software engineering, and computational biology groups to co-define data standards and conventions.

Qualifications & Requirements
  • Demonstrated experience building multi-agent workflows or LLM workflows using tools/frameworks such as LangGraph or LlamaIndex, including tool/function calling and asynchronous task execution.
  • Strong Python skills for data manipulation, working with APIs and databases, and handling heterogeneous data formats.
  • Familiarity with dataset versioning approaches (e.g., DVC, lakeFS, or equivalent).
  • Comfortable with or showing a strong willingness to learn common omics data formats like AnnData, H5AD, and TileDB.
  • No deep bioinformatics expertise required; just a basic conceptual understanding of different modalities (e.g., RNA-seq vs. scRNA-seq vs. WES; genomics vs. transcriptomics vs. proteomics vs. metabolomics).
  • Comfortable writing unit and functional tests to ensure data processing workflows are reliable and reproducible.
  • Degree in a technical field or equivalent practical experience.
  • Must be Authorized to work in the United States without Sponsorship.
Nice to Have
  • Experience deploying agent workflows as a shared service (e.g., FastAPI or MCP endpoints).
  • Exposure to cloud platforms (AWS, GCP) and containerization (Docker).
  • Familiarity with scientific workflow managers such as Nextflow or Snakemake.

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