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Data Engineer Google Jobs in Virginia (NOW HIRING)

Pwc

Data Engineer - Senior Manager

Richmond, VA

$124K - $280K/yr

... Google Professional Cloud Architect, GCP Data Engineer Microsoft Azure Solutions Architect, Azure Data Engineer Associate, Snowflake Core, Snowflake Architect, Databricks Data Engineer Associate] is ...

RecruitTalent LLC.

Data Scientist

Fredericksburg, VA · On-site

$60 - $70/hr

Google Professional Data Engineer or AWS Certified Data Analytics - Specialty * Certified Analytics Professional (CAP) - INFORMS * Lean Six Sigma Green Belt (for data-driven process improvement)

SZNS Solutions LLC

Data Engineer

Reston, VA · On-site

$119K - $143K/yr

Founded by ex-Googlers with engineers from Google, Amazon, and Capital One, SZNS differentiates itself particularly in AI, data engineering, blockchain, and cloud-native software application ...

SZNS Solutions LLC

Data Engineer

Reston, VA · On-site

$119K - $143K/yr

Founded by ex-Googlers with engineers from Google, Amazon, and Capital One, SZNS differentiates itself particularly in AI, data engineering, blockchain, and cloud-native software application ...

SZNS Solutions LLC

Data Engineer

Reston, VA · On-site

$119K - $143K/yr

Founded by ex-Googlers with engineers from Google, Amazon, and Capital One, SZNS differentiates itself particularly in AI, data engineering, blockchain, and cloud-native software application ...

Accenture Federal Services

Data Engineer

Arlington, VA · On-site

$93K - $176K/yr

AWS Glue, Google Cloud Dataflow, Azure Data Factory) * Experience with Cloud data warehousing ... Data engineering certification such as Palantir Foundry Data Engineer, Azure Data Engineer ...

ECS

Data Engineer

Ashburn, VA · On-site

$145K - $160K/yr

The Data Engineer supports the construction and day-to-day operation of Customs and Border ... Google Cloud Platform (GCP). * Working knowledge of Python and/or SQL, with familiarity with at ...

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All JobsData Engineer Google JobsData Engineer Google Jobs in Virginia

Data Engineer Google information

See Virginia salary details

$44.1K

$128.6K

$176K

How much do data engineer google jobs pay per year?

As of Aug 27, 2026, the average yearly pay for data engineer google in Virginia is $128,604.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,300.00 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 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.

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.

What are popular job titles related to Data Engineer Google jobs in Virginia?

For Data Engineer Google jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Data Engineer Google jobs in Virginia look for?

The top searched job categories for Data Engineer Google jobs in Virginia are:

Data Engineer Google jobs near you
Infographic showing various Data Engineer Google job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $128,604 per year, or $61.8 per hour.

Google Cloud Platform Data Engineer

Interon IT Solutions LLC

Chantilly, VA • On-site

$117K - $140K/yr

Other

Posted 6 days ago

Job description

#W2 role

Role: Senior Google Cloud Platform Data Engineer
Location:Remote
Experience: 8+ years

Job Description

Our client is looking for an experienced Google Cloud Platform Data Engineer to build and support cloud-based data solutions for healthcare, pharmacy, claims, member, and operational data.

This is a hands-on development role. The engineer will work with architects, analysts, product owners, and other engineering teams to build reliable batch and real-time data pipelines on Google Cloud Platform.

Responsibilities

  • Design, develop, and maintain scalable data pipelines using Google Cloud Platform services.

  • Build batch and streaming solutions using Dataflow, Pub/Sub, BigQuery, Cloud Storage, Dataproc, and Cloud Composer.

  • Develop data-processing applications using Python, SQL, Spark, and Apache Beam.

  • Create BigQuery tables, views, stored procedures, and data models.

  • Apply partitioning and clustering strategies to improve BigQuery performance and cost.

  • Ingest and transform healthcare, pharmacy, claims, member, provider, and operational data.

  • Build data validation, reconciliation, error-handling, and monitoring processes.

  • Troubleshoot pipeline failures, data-quality issues, and performance problems.

  • Support data migration from legacy and on-premises platforms to Google Cloud Platform.

  • Protect PHI, PII, and other sensitive information using appropriate security and access controls.

  • Develop automated build and deployment pipelines using Git, Jenkins or GitLab CI/CD, and Terraform.

  • Participate in code reviews, production releases, and operational support.

Required Qualifications

  • 8+ years of data engineering or software development experience.

  • 4+ years of hands-on experience with Google Cloud Platform data services.

  • Strong experience with BigQuery, Dataflow, Pub/Sub, Cloud Storage, Dataproc, and Cloud Composer.

  • Advanced Python and SQL development skills.

  • Experience with Spark, Apache Beam, and Airflow.

  • Strong understanding of ETL/ELT, data warehousing, data lakes, and distributed data processing.

  • Experience building both batch and streaming data pipelines.

  • Experience with Docker, Kubernetes, Terraform, Git, and CI/CD.

  • Strong troubleshooting and communication skills.

Preferred Qualifications

  • Healthcare, pharmacy, PBM, claims, or health insurance experience.

  • Understanding of HIPAA, PHI, and PII requirements.

  • Experience with dbt, Dataplex, Data Catalog, Cloud Run, Cloud Functions, or Looker.

  • Google Professional Data Engineer certification.

Apply