Data Science Engineer Jobs at Google with Visa Sponsorship
Data Science Engineer jobs at Google sit at the intersection of large-scale machine learning infrastructure and applied research, requiring deep expertise in ML systems, statistical modeling, and distributed computing. Google has a well-established sponsorship pathway for this function across H-1B visa, H-1B1 visa, and E-3 visa categories.
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Get Access To All JobsINTRODUCTION
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
ROLE AND RESPONSIBILITIES
- Design and implement secure, scalable, and reliable data solutions, including data models, pipelines, and infrastructure frameworks.
- Perform exploratory data analysis and leverage machine learning models to enable data-driven insights and business solutions.
- Create and deliver technical enablement materials, including best practice guides, sample code, presentations, and educational workshops.
- Collaborate with product management, engineering, and data science teams to influence product development and drive technical excellence.
- Advise customers on migrating and optimizing database systems and data processing workloads on Google Cloud Platform. Analyze cloud database environments and consult on the optimal design for performance and deployment on Google Cloud Platform.
BASIC QUALIFICATIONS
- Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or a related field, and 1 year of experience in the job offered or in a Data Engineer-related occupation.
- Position requires 1 year of experience in the following:
- Database performance tuning, including SQL query optimization
- Database management using tools for backup, recovery, and partitioning
- Large-scale data migration from on-premise or data center environments to cloud
- Development of ETL or ELT workflows, data pipeline design, and dimensional data modeling
- Software development in Java, C++, Python, Go, or JavaScript
COMPENSATION
- The US base salary range for this full-time position is $123,900 - $151,000 + 15% bonus target + equity + benefits determined by role, level, and location. Individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training.
LOCATION
Position reports to the Google Austin, TX office & may allow for a hybrid schedule as per Google policy.
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
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
ROLE AND RESPONSIBILITIES
- Design and implement secure, scalable, and reliable data solutions, including data models, pipelines, and infrastructure frameworks.
- Perform exploratory data analysis and leverage machine learning models to enable data-driven insights and business solutions.
- Create and deliver technical enablement materials, including best practice guides, sample code, presentations, and educational workshops.
- Collaborate with product management, engineering, and data science teams to influence product development and drive technical excellence.
- Advise customers on migrating and optimizing database systems and data processing workloads on Google Cloud Platform. Analyze cloud database environments and consult on the optimal design for performance and deployment on Google Cloud Platform.
BASIC QUALIFICATIONS
- Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or a related field, and 1 year of experience in the job offered or in a Data Engineer-related occupation.
- Position requires 1 year of experience in the following:
- Database performance tuning, including SQL query optimization
- Database management using tools for backup, recovery, and partitioning
- Large-scale data migration from on-premise or data center environments to cloud
- Development of ETL or ELT workflows, data pipeline design, and dimensional data modeling
- Software development in Java, C++, Python, Go, or JavaScript
COMPENSATION
- The US base salary range for this full-time position is $123,900 - $151,000 + 15% bonus target + equity + benefits determined by role, level, and location. Individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training.
LOCATION
Position reports to the Google Austin, TX office & may allow for a hybrid schedule as per Google policy.
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 103+ Data Science Engineer Jobs at Google
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Get Access To All JobsTips for Finding Data Science Engineer Jobs at Google
Align your portfolio with Google's ML infrastructure
Google's Data Science Engineer interviews weight systems-level ML experience heavily. Before applying, build or document projects involving large-scale model training, feature engineering pipelines, or distributed data processing using tools like BigQuery, TensorFlow, or Apache Beam.
Target teams with consistent sponsorship history
Google's sponsorship activity varies across product areas. Research which teams, like Google DeepMind, Google Cloud AI, or Search infrastructure, have filed the most LCAs with the DOL. Those teams signal active headcount growth and established sponsorship processes.
Distinguish your visa category early in outreach
Australian citizens should proactively flag E-3 eligibility when contacting recruiters. Google's recruiting coordinators are familiar with E-3 processing, and clarifying your category upfront removes ambiguity about cap constraints that apply to standard H-1B candidates.
Use Migrate Mate to find open roles that list sponsorship
Filtering for sponsorship-confirmed Data Science Engineer openings at Google saves significant time. Migrate Mate surfaces roles where Google has indicated willingness to sponsor, so you're applying where a pathway already exists rather than guessing from a general job listing.
Prepare for the LCA prevailing wage conversation
Google's offers for Data Science Engineers must meet DOL prevailing wage requirements tied to the job's location and SOC code. If your offer comes in below Level III or IV wage thresholds for your metro area, that affects what USCIS will accept on your I-129 petition.
Time your application relative to the H-1B registration window
If you need H-1B sponsorship, Google must register you in USCIS's annual lottery that opens each March. Starting your interview process in January or February gives your offer letter and paperwork time to be completed before registration closes.
Frequently Asked Questions
Does Google sponsor H-1B visas for Data Science Engineers?
Yes, Google sponsors H-1B visas for Data Science Engineer roles. Google files H-1B petitions through the standard USCIS lottery process each April for cap-subject candidates, with an October 1 start date. Google also files for cap-exempt situations where applicable, such as candidates transferring from qualifying research institutions. The role must meet DOL prevailing wage requirements for the position's location.
How do I apply for Data Science Engineer jobs at Google?
Applications go through Google's careers portal, but most successful candidates connect with a recruiter or get a referral before applying cold. The interview process for Data Science Engineers typically includes a recruiter screen, technical phone screens covering ML systems and coding, and a virtual onsite with rounds focused on machine learning design, data analysis, and coding. You can browse sponsorship-confirmed openings at Google through Migrate Mate before applying.
Which visa types does Google commonly use for Data Science Engineer roles?
Google sponsors H-1B, H-1B1 visa, and E-3 visas for Data Science Engineer positions. H-1B is the most common path and requires clearing the annual USCIS lottery. H-1B1 is available to Chilean and Singaporean nationals and bypasses the lottery entirely. E-3 is exclusive to Australian citizens and also avoids the H-1B cap, making it a faster path for Australians already in the interview process.
What qualifications does Google expect for a Data Science Engineer role?
Google's Data Science Engineer roles typically require a master's or PhD in computer science, statistics, or a related quantitative field, though candidates with a bachelor's degree and substantial industry experience are considered. You're expected to demonstrate proficiency in SQL, Python, and at least one ML framework, plus experience designing and deploying models at scale. Published research or open-source contributions in ML carry significant weight in the hiring process.
How long does it take to get sponsored for a Google Data Science Engineer role?
Timeline depends on which visa category applies. For H-1B, factor in the March lottery registration, a potential six-month wait until the October 1 start date, and USCIS adjudication time, which can run three to five months under standard processing. E-3 and H-1B1 visa move faster since they skip the lottery and can be filed year-round, with consular processing at a U.S. embassy typically taking two to six weeks after your LCA is certified by the DOL.