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Data Engineer Google Jobs (NOW HIRING)

Infinitive Inc

Data Engineer

Decatur, GA · On-site

$111K - $134K/yr

Advanced degree or relevant professional certifications (e.g., AWS Certified Data Engineer, Google Cloud Certified Professional Data Engineer, Azure Data Engineer Associate) preferred. Infinitive is ...

Intellisoft Technologies

Data Engineer

Farmers Branch, TX

$110K - $132K/yr

Data Engineering Google Cloud Platform (GCP) Engineer is responsible to develop and deliver ... effective cloud solutions for different business units. This position requires knowledge and ...

SHI

Solutions Engineer - Google AI

Austin, TX · On-site

Job Summary The Solutions Engineer - Google AI collaborates with account and specialty teams to ... They will represent the Google AI portfolio (Gemini Enterprise, AI Applications, Vertex AI, Data ...

Google

DFT Engineer, Google Cloud

Sunnyvale, CA · On-site

$144K - $191K/yr

... Data Center operations, systems research, and much more. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $138000 - $198000 ...

Google

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

... Data Engineer-related occupation. * Position requires 1 year of experience in the following ... We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools ...

Google

Software Engineer, Google Cloud Storage

Raleigh, NC · On-site

$58.25 - $75.75/hr

Google is bringing our cloud anywhere with Google Distributed Cloud (GDC) in your data center, at ... developers build more sustainably. Customers in more than 200 countries and territories turn to ...

Programmers.io

AI/ML Engineer

Scottsdale, AZ · On-site

Google Cloud Professional Machine Learning Engineer Google Cloud Professional Data Engineer AWS Certified Machine Learning Specialty Certified Kubernetes Admin(CKA) Google Professional Cloud ...

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Data Engineer Google information

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$44.5K

$129.7K

$177.5K

How much do data engineer google jobs pay per year?

As of Jun 21, 2026, the average yearly pay for data engineer google in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What does a Data Engineer at Google do?

A Data Engineer at Google designs, builds, and manages systems that collect, store, and process large volumes of data. Their responsibilities include creating data pipelines, ensuring data quality, and optimizing data architectures to support analytics and machine learning initiatives. They work closely with data scientists, analysts, and other engineers to ensure that data is accessible, reliable, and efficiently processed for various business needs.

How do Data Engineers at Google typically collaborate with data scientists and software engineers?

At Google, Data Engineers work closely with both data scientists and software engineers to build robust, scalable data pipelines and infrastructure. Data Engineers are responsible for ensuring that data is clean, accessible, and optimized for analytics, often translating business needs into technical solutions. Regular collaboration happens through cross-functional meetings, design sessions, and code reviews, where Data Engineers provide expertise in data modeling, ETL processes, and system optimization. This collaborative environment promotes innovation, knowledge sharing, and the successful deployment of data-driven products.

What engineers make $500,000?

Senior data engineers, especially those with extensive experience, advanced skills in cloud platforms, and expertise in big data tools, can earn $500,000 or more annually. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or in high-cost-of-living areas.

What are the key skills and qualifications needed to thrive as a Data Engineer at Google, and why are they important?

To thrive as a Data Engineer at Google, you need strong programming skills (especially in Python, Java, or Scala), expertise in data modeling, and a solid understanding of distributed systems, typically supported by a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP), BigQuery, SQL, Apache Spark, and relevant data engineering certifications is highly valued. Analytical thinking, effective communication, and problem-solving abilities are crucial soft skills for collaborating across teams and translating business requirements into technical solutions. These skills ensure the reliable design, optimization, and scalability of data systems critical to Google's innovation and decision-making.

Does Google hire data engineers?

Yes, Google hires data engineers to develop and maintain data pipelines, manage large-scale data systems, and support data-driven decision-making. Candidates typically need strong skills in SQL, Python, and cloud platforms like Google Cloud, along with relevant experience in data architecture and engineering. Google regularly recruits data engineers across various teams and locations.

What is the difference between Data Engineer Google vs Data Engineer Amazon?

AspectData Engineer GoogleData Engineer Amazon
Required CredentialsBachelor's in CS or related, Google Cloud certifications often preferredBachelor's in CS or related, AWS certifications common
Work EnvironmentGoogle Cloud Platform, large-scale data systems, collaborative teamsAWS cloud services, large data pipelines, cross-functional teams
Employer & Industry UsageGoogle, tech and internet servicesAmazon, e-commerce and cloud services
Search & Comparison IntentHigh overlap in cloud data engineering rolesSimilar roles in cloud data engineering

Both Data Engineer Google and Data Engineer Amazon roles require strong data processing skills, cloud platform knowledge, and relevant certifications. While Google emphasizes Google Cloud Platform expertise, Amazon focuses on AWS. Both roles are integral to their respective companies' data infrastructure, with similar work environments and industry usage, making them common comparison points for data engineering careers in cloud environments.

How much does a Data Engineer at Google make?

A Data Engineer at Google typically earns a base salary ranging from $100,000 to $150,000 annually, with total compensation often including bonuses and stock options that can significantly increase overall earnings. Compensation varies based on experience, location, and level within the company, and the role often requires proficiency in tools like SQL, Python, and cloud platforms such as Google Cloud Platform.

Is L7 a good level at Google?

At Google, L7 is considered a senior leadership level, typically involving significant technical expertise and management responsibilities. It is a high-level position that often requires extensive experience, strong problem-solving skills, and proficiency with tools like BigQuery and Dataflow. L7 is generally regarded as a prestigious and well-compensated level within the company.
More about Data Engineer Google jobs
What cities are hiring for Data Engineer Google jobs? Cities with the most Data Engineer Google job openings:
What states have the most Data Engineer Google jobs? States with the most job openings for Data Engineer Google jobs include:
What job categories do people searching Data Engineer Google jobs look for? The top searched job categories for Data Engineer Google jobs are:
Data Engineer Google jobs near you
Infographic showing various Data Engineer Google job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Data Engineer Google Cloud Platform (mid-level)

Relanto, Inc.

San Francisco, CA • Hybrid

$134K - $162K/yr

Other

Posted 19 days ago

Job description

Role: Data Engineer – Google Cloud Platform (mid-level)

Duration: 6+ months

Location: Bay Area, CA (hybrid)

Job Summary:

We are looking for a skilled Data Engineer with 2–4 years of experience in building and maintaining scalable data pipelines and cloud-based data platforms on Google Cloud Platform (Google Cloud Platform). The ideal candidate should have hands-on expertise in Python, SQL, PySpark, BigQuery, Airflow, and modern ETL/ELT frameworks. 

The role involves working closely with analytics, business, and engineering teams to enable reliable and scalable data solutions.  

Required Skills:

  • 2–4 years of experience in Data Engineering or related roles 
  • Strong hands-on experience with Python and SQL 
  • Experience with PySpark and distributed data processing 
  • Good knowledge of BigQuery and Google Cloud Platform services 
  • Experience with Apache Airflow for orchestration 
  • Hands-on experience with dbt for data transformation and modeling 
  • Understanding of ETL/ELT frameworks and data warehousing concepts 
  • Familiarity with Google Cloud Platform services such as: 
  • BigQuery 
  • Cloud Storage 
  • Dataproc 
  • Composer 
  • Pub/Sub 
  • Experience with Git and CI/CD practices 
  • Strong analytical and problem-solving skills 

Good to Have:

  • Exposure to streaming pipelines using Kafka or Pub/Sub 
  • Understanding of data governance and security concepts 
  • Experience with Terraform or Infrastructure as Code 
  • Knowledge of containerization (Docker/Kubernetes) 

Preferred Qualification:

  • Bachelor’s degree in Computer Science, Engineering, or related field 
  • Google Cloud Platform certification is a plus 

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