Senior Data Science Engineer Jobs at Google with Visa Sponsorship
Senior Data Science Engineer jobs at Google sit at the intersection of large-scale machine learning infrastructure and product impact. Google has a well-established sponsorship process for this function, supporting candidates through H-1B visa, H-1B1 visa, and E-3 visa pathways as part of its standard technical hiring.
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Get Access To All JobsINTRODUCTION
Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Chicago, IL, USA; New York, NY, USA; Irvine, CA, USA.
MINIMUM QUALIFICATIONS:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience coding in Python and SQL.
- 5 years of experience working with machine learning operations (MLOps) and large language model operations (LLMOps) principles and data infrastructure, including deploying text processing and embedding pipelines.
- 5 years of experience designing and deploying data pipelines, including managing data schemas and processing unstructured text data for machine learning (ML) workflows.
PREFERRED QUALIFICATIONS:
- Experience with data schemas.
- Experience with google colaboratory (Colab), TensorFlow, Tensor Processing Units (TPUs), and agentic tools and platforms for processing unstructured text data.
- Experience with LLM orchestration and agentic infrastructure.
- Proficiency in SQL and Python.
- Understanding of MLOps/LLMOps principles to ensure the scalable and reliable deployment of text processing and embedding pipelines.
ABOUT THE JOB
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.
As a part of the Go-to-Market (GTM), you will serve as the intelligence partner for product teams, transforming massive volumes of unstructured conversational data into quantified, trusted insights that bridge the gap between customer feedback and product decisions, as this is a high-visibility initiative critical for accelerating the Ads product adoption flywheel and shaping Go-to-Market (GTM) strategy for priority products.
As a Senior Data Engineer, you will own and architect the foundational infrastructure that transforms unstructured customer feedback into quantified strategic assets. You will help us move towards scalable, automated pipelines that integrate sales transcripts with critical Business Intelligence (BI). You will pioneer our transition towards more flexible workflows, developing the core infrastructure and platforms that multiply our data science team's capacity, agility, and impact through end-to-end delivery of production-ready solutions.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
$156000 - $227000 (USD) + 15% bonus target + bonus + equity + benefits.
Learn more about benefits at Google.
Responsibilities
- Design and maintain pipelines to ingest, clean, and process massive volumes of unstructured data, including business transcripts and support cases, into reliable analytical datasets.
- Architect and deploy advanced platforms and tooling that empower the team to leverage autonomous AI agents and Large Language Models (LLMs) for intelligent routing and automated insights.
- Develop internal libraries and self-serve frameworks that streamline Natural Language Processing (NLP) and causal analysis, significantly reducing operational friction and enhancing team productivity.
- Manage and optimize embedding workflows using TensorFlow and Tensor Processing Units (TPUs), ensuring efficient processing that bypasses standard API constraints for high-volume data.
- Implement automated monitoring, alerting, and rigorous data quality checks to guarantee the security, reliability, and governance of high-stakes analytical assets.
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
Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Chicago, IL, USA; New York, NY, USA; Irvine, CA, USA.
MINIMUM QUALIFICATIONS:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience coding in Python and SQL.
- 5 years of experience working with machine learning operations (MLOps) and large language model operations (LLMOps) principles and data infrastructure, including deploying text processing and embedding pipelines.
- 5 years of experience designing and deploying data pipelines, including managing data schemas and processing unstructured text data for machine learning (ML) workflows.
PREFERRED QUALIFICATIONS:
- Experience with data schemas.
- Experience with google colaboratory (Colab), TensorFlow, Tensor Processing Units (TPUs), and agentic tools and platforms for processing unstructured text data.
- Experience with LLM orchestration and agentic infrastructure.
- Proficiency in SQL and Python.
- Understanding of MLOps/LLMOps principles to ensure the scalable and reliable deployment of text processing and embedding pipelines.
ABOUT THE JOB
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.
As a part of the Go-to-Market (GTM), you will serve as the intelligence partner for product teams, transforming massive volumes of unstructured conversational data into quantified, trusted insights that bridge the gap between customer feedback and product decisions, as this is a high-visibility initiative critical for accelerating the Ads product adoption flywheel and shaping Go-to-Market (GTM) strategy for priority products.
As a Senior Data Engineer, you will own and architect the foundational infrastructure that transforms unstructured customer feedback into quantified strategic assets. You will help us move towards scalable, automated pipelines that integrate sales transcripts with critical Business Intelligence (BI). You will pioneer our transition towards more flexible workflows, developing the core infrastructure and platforms that multiply our data science team's capacity, agility, and impact through end-to-end delivery of production-ready solutions.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
$156000 - $227000 (USD) + 15% bonus target + bonus + equity + benefits.
Learn more about benefits at Google.
Responsibilities
- Design and maintain pipelines to ingest, clean, and process massive volumes of unstructured data, including business transcripts and support cases, into reliable analytical datasets.
- Architect and deploy advanced platforms and tooling that empower the team to leverage autonomous AI agents and Large Language Models (LLMs) for intelligent routing and automated insights.
- Develop internal libraries and self-serve frameworks that streamline Natural Language Processing (NLP) and causal analysis, significantly reducing operational friction and enhancing team productivity.
- Manage and optimize embedding workflows using TensorFlow and Tensor Processing Units (TPUs), ensuring efficient processing that bypasses standard API constraints for high-volume data.
- Implement automated monitoring, alerting, and rigorous data quality checks to guarantee the security, reliability, and governance of high-stakes analytical assets.
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 Senior Data Science Engineer Jobs at Google
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Senior Data Science Engineer Jobs at Google.
Get Access To All JobsTips for Finding Senior Data Science Engineer Jobs at Google
Align Your Portfolio With Google Scale
Google's hiring bar for Senior Data Science Engineers prioritizes experience with distributed systems and ML at scale. Frame past projects around data volume, model deployment pipelines, and measurable product impact rather than academic or small-dataset work.
Target the Right Google Org Early
Data science roles at Google vary significantly by org: Search, Ads, Cloud, and DeepMind each have different tooling and scope expectations. Research which team's technical stack matches your background before applying, since internal referrals carry more weight within specific orgs.
Confirm Your Visa Category Before Accepting
Google sponsors H-1B, H-1B1 visa, and E-3 visas for this role. If you're Australian or Chilean, confirm with the recruiter that your category is available for the specific team and location, since not every Google office processes all three visa types.
Prepare for the H-1B Cap Timeline
If your role requires a cap-subject H-1B, USCIS registration opens in March for an October 1 start. Google typically files early, but you and your recruiter need to align on offer timing so your start date accommodates the lottery and approval window.
Secure Documentation of Specialized Degree Equivalency
USCIS scrutinizes specialty occupation claims for data science roles where job postings accept multiple degree fields. If your degree is in a non-traditional field like physics or economics, gather official transcripts and a credential evaluation before your petition is filed.
Use Migrate Mate to Surface Sponsorship Openings
Google posts Senior Data Science Engineer openings across multiple locations, and sponsorship eligibility isn't always stated upfront. Use Migrate Mate to filter and track Google roles confirmed to offer visa sponsorship, so you focus your prep on positions where you're actually eligible.
Frequently Asked Questions
Does Google sponsor H-1B visas for Senior Data Science Engineers?
Yes, Google sponsors H-1B visas for Senior Data Science Engineers as part of its standard technical hiring process. Google's immigration team works with outside counsel to handle petition filing, and sponsorship is typically included in your offer package. If you're subject to the H-1B cap, your offer and start date will be structured around the USCIS registration and lottery timeline.
Which visa types does Google use for Senior Data Science Engineer roles?
Google sponsors H-1B, H-1B1 visa, and E-3 visas for Senior Data Science Engineer positions. H-1B is the most common path for non-Australian, non-Chilean nationals. Australian citizens can pursue the E-3, which has no lottery and a dedicated annual allocation. Chilean nationals can access the H-1B1. Each category has different eligibility requirements and processing steps, so confirm which applies to you early in the recruiting process.
How do I apply for Senior Data Science Engineer jobs at Google?
Applications go through Google's careers portal, but the process is highly selective at the senior level. Most successful candidates have a strong referral or prior Google-adjacent network connection. The interview loop typically includes a coding screen, two to three technical rounds focused on statistics, ML system design, and SQL, plus a Googleyness and leadership round. Tailoring your resume to Google's specific data infrastructure work substantially improves your chances of passing the initial recruiter screen.
What qualifications does Google expect for Senior Data Science Engineers?
Google expects a graduate degree in computer science, statistics, applied mathematics, or a closely related field for senior-level roles, though exceptional candidates with a bachelor's and extensive industry experience are considered. You'll need demonstrated experience building production ML systems, working with large-scale data pipelines, and influencing cross-functional product decisions. Proficiency in Python, SQL, and distributed computing frameworks like Spark or BigQuery is standard at this level.
How do I find Senior Data Science Engineer jobs at Google that offer visa sponsorship?
Google lists roles on its careers site, but sponsorship availability isn't always explicit in job descriptions. Migrate Mate filters Senior Data Science Engineer roles at Google by confirmed visa sponsorship type, so you can identify H-1B, H-1B1 visa, or E-3 eligible openings without manually contacting recruiters for each position. This saves significant time, especially if you're working against an OPT or grace period deadline.