Data Engineer Jobs at Google with Visa Sponsorship
Data Engineer roles at Google sit at the intersection of large-scale infrastructure and product impact, spanning pipelines, warehousing, and real-time data systems. Google has a well-established sponsorship process for this function, supporting H-1B, H-1B1, and E-3 candidates through structured legal and recruiting teams.
See All Data Engineer at Google JobsOverview
Showing 5 of 246+ Data Engineer Jobs at Google jobs


Have you applied for this role?


Have you applied for this role?


Have you applied for this role?


Have you applied for this role?


Have you applied for this role?
See all 246+ Data Engineer Jobs at Google
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Engineer Jobs at Google.
Get Access To All Jobs
INTRODUCTION
gTech’s Product and Tools Operations team (gPTO) leverages deep user, operational, and technical insights to innovate Google's Ads products into customer experiences that are so intuitive (or automated) that they require no support at all. gPTO partners closely with gTech’s Support, Professional Services, Product Management, and Engineering teams to innovate and simplify our Ads products and build the productivity tools ecosystem for gTech users.
In this role, you will support the GASP team which builds technology to protect Geo assets at scale. As a Data Engineer, you will build and manage data pipelines to ensure data sources can be consumed by the Geo Anti-Scraping Program (GASP) for abuse and scraping detection, monitoring and measurement. The Geo team is focused on building the most accurate, comprehensive, and useful maps for our users, through products like Maps, Earth, Street View, Google Maps Platform, and more. Every month, more than a billion people rely on Maps services to explore the world and navigate their daily lives.
The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world.
The US base salary range for this full-time position is $156,000-$226,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
BASIC QUALIFICATIONS:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience designing, building, and managing production-grade ETL pipelines.
- Experience writing readable, structured code (e.g., Python, Java) and applying AI/ML libraries/frameworks (e.g., TensorFlow, Vertex AI) within data systems.
- Experience applying AI/ML techniques to anti-abuse, security, or fraud detection.
PREFERRED QUALIFICATIONS:
- Experience with AI to drive automation for data pipelines and data quality.
- Experience with data logging, monitoring, and analysis tools.
- Familiarity with distributed systems.
- Ability to manage project timelines and deliverables effectively.
- Understanding of bot detection techniques and adversarial machine learning.
- Excellent stakeholder engagement skills, with experience working with both internal teams and external vendors.
Responsibilities
- Architect, build, and maintain data pipelines to ingest, process, and transform logs and signals from various Geo services for scraping detection and analysis.
- Implement and manage data quality frameworks, leveraging AI and automation to enhance data ingestion, ensure data integrity, and improve the accuracy of anti-scraping models and analytics.
- Develop and maintain curated datasets, reports, queries, and dashboards to support client users in understanding and mitigating scraping threats.
- Drive the creation of automated solutions and self-service tools to accelerate data-driven decision-making and improve the efficiency of anti-scraping operations and partner care experiences.
- Provide operational support for anti-scraping data systems, including performance monitoring, post-launch issue resolution, proactive planning for dependency changes and system migrations, while defining and driving the long-term technical goal and roadmap for a scalable, resilient, and cost-effective anti-scraping data infrastructure for Google Maps.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

INTRODUCTION
gTech’s Product and Tools Operations team (gPTO) leverages deep user, operational, and technical insights to innovate Google's Ads products into customer experiences that are so intuitive (or automated) that they require no support at all. gPTO partners closely with gTech’s Support, Professional Services, Product Management, and Engineering teams to innovate and simplify our Ads products and build the productivity tools ecosystem for gTech users.
In this role, you will support the GASP team which builds technology to protect Geo assets at scale. As a Data Engineer, you will build and manage data pipelines to ensure data sources can be consumed by the Geo Anti-Scraping Program (GASP) for abuse and scraping detection, monitoring and measurement. The Geo team is focused on building the most accurate, comprehensive, and useful maps for our users, through products like Maps, Earth, Street View, Google Maps Platform, and more. Every month, more than a billion people rely on Maps services to explore the world and navigate their daily lives.
The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world.
The US base salary range for this full-time position is $156,000-$226,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
BASIC QUALIFICATIONS:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience designing, building, and managing production-grade ETL pipelines.
- Experience writing readable, structured code (e.g., Python, Java) and applying AI/ML libraries/frameworks (e.g., TensorFlow, Vertex AI) within data systems.
- Experience applying AI/ML techniques to anti-abuse, security, or fraud detection.
PREFERRED QUALIFICATIONS:
- Experience with AI to drive automation for data pipelines and data quality.
- Experience with data logging, monitoring, and analysis tools.
- Familiarity with distributed systems.
- Ability to manage project timelines and deliverables effectively.
- Understanding of bot detection techniques and adversarial machine learning.
- Excellent stakeholder engagement skills, with experience working with both internal teams and external vendors.
Responsibilities
- Architect, build, and maintain data pipelines to ingest, process, and transform logs and signals from various Geo services for scraping detection and analysis.
- Implement and manage data quality frameworks, leveraging AI and automation to enhance data ingestion, ensure data integrity, and improve the accuracy of anti-scraping models and analytics.
- Develop and maintain curated datasets, reports, queries, and dashboards to support client users in understanding and mitigating scraping threats.
- Drive the creation of automated solutions and self-service tools to accelerate data-driven decision-making and improve the efficiency of anti-scraping operations and partner care experiences.
- Provide operational support for anti-scraping data systems, including performance monitoring, post-launch issue resolution, proactive planning for dependency changes and system migrations, while defining and driving the long-term technical goal and roadmap for a scalable, resilient, and cost-effective anti-scraping data infrastructure for Google Maps.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
See all 246+ Data Engineer at Google jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Engineer at Google roles.
Get Access To All JobsTips for Finding Data Engineer Jobs at Google Jobs
Tailor your portfolio to Google's stack
Google's Data Engineer roles lean heavily on BigQuery, Dataflow, and Pub/Sub. Showcasing hands-on experience with these tools, or their open-source equivalents like Apache Beam, signals immediate fit and reduces friction in technical screening.
Align your application to Google's leveling system
Google evaluates Data Engineers against internal levels (L3 to L6+). Applying at the right level matters for sponsorship, since more senior roles often move through offer and filing stages faster due to established headcount and legal budget.
Understand the H-1B cap timing relative to your start date
If you need a new H-1B, USCIS registration opens in March for an October 1 start. Plan your Google interview process so an offer lands before the registration window, giving your sponsor enough runway to file on your behalf.
Use Migrate Mate to surface open Data Engineer roles at Google
Data Engineer openings at Google move quickly and aren't always easy to filter by sponsorship type. Use Migrate Mate to browse current listings at Google filtered by visa category, so you're applying to roles where sponsorship is already confirmed.
Data Engineer at Google jobs are hiring across the US. Find yours.
Find Data Engineer at Google JobsFrequently Asked Questions
Does Google sponsor H-1B visas for Data Engineers?
Yes, Google sponsors H-1B visas for Data Engineer roles. Google has dedicated immigration legal teams that manage the petition process from Labor Condition Application filing with the DOL through USCIS adjudication. If you need H-1B sponsorship, you'll want to confirm the specific role is eligible during your recruiter screening call, as sponsorship decisions are made at the team level.
How do I apply for Data Engineer jobs at Google?
Applications go through Google's careers portal, where you can filter by job function and location. For the strongest chance of being seen, tailor your resume to highlight experience with distributed data systems and Google Cloud tooling. You can also browse current Data Engineer openings at Google filtered by visa sponsorship type on Migrate Mate, which surfaces roles where sponsorship has been confirmed.
Which visa types does Google commonly sponsor for Data Engineer roles?
Google sponsors H-1B, H-1B1, and E-3 visas for Data Engineer positions. H-1B is the most common pathway for most nationalities. H-1B1 applies to nationals of Singapore and Chile, and E-3 applies exclusively to Australian citizens. Each visa type has different filing mechanics and timelines, so clarifying your category early in the recruiting process helps Google's legal team plan accordingly.
What qualifications does Google expect for sponsored Data Engineer roles?
Google's Data Engineer roles typically require a bachelor's degree or higher in computer science, engineering, or a related field, which also satisfies the specialty occupation requirement for H-1B and E-3 petitions. Beyond credentials, Google's technical bar emphasizes hands-on experience with large-scale data pipelines, SQL and distributed systems, and familiarity with cloud-native tooling. Passing the technical interview loop is the main filter, not just degree level.
How do I navigate the timeline between offer and visa filing at Google?
After an offer is accepted, Google's immigration team initiates the visa petition process, which typically starts with the employer filing a Labor Condition Application with the DOL. For H-1B transfers from another sponsoring employer, you can start work as soon as USCIS receives the petition. For new H-1B cap cases, the October 1 start date is fixed, so build at least six months of runway into your job search timeline.
See which Data Engineer at Google employers are hiring and sponsoring visas right now.
Search Data Engineer at Google Jobs