Data Engineer Visa Sponsorship Jobs in Washington
Washington is one of the strongest states for data engineer visa sponsorship, driven by a dense concentration of technology employers in the Seattle metro area. Companies like Microsoft, Amazon, and Meta maintain large data engineering teams and have established sponsorship programs. Smaller high-growth firms in cloud infrastructure, e-commerce, and enterprise software round out a deep hiring market.
Find Data Engineer JobsOverview
Showing 5 of 204+ Data Engineer Jobs in Washington with Visa Sponsorship
See all 204+ Data Engineer Jobs in Washington with Visa Sponsorship
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Engineer Jobs in Washington with Visa Sponsorship.
Get Access To All JobsDESCRIPTION
Want to apply data science to one of Amazon's fastest-growing payment businesses, serving millions of sellers and buyers across 20+ global marketplaces? As a Data Scientist I on the cross-border payments science team, you will build and deploy production models that power real-time FX risk monitoring, generative AI seller chatbots, and multi-agent AI tools. You will work end-to-end—from problem framing through production deployment on AWS—delivering solutions that directly influence billion-dollar payment flows. This is a high-visibility, small-team environment where your work informs senior leadership decisions and creates measurable impact for customers worldwide.
Key job responsibilities
- Build, tune, and evaluate large language models and generative AI applications, including seller-facing chatbots and multi-agent AI tools for the cross-border payments business.
- Develop and deploy real-time statistical and machine learning models for FX risk monitoring, validating your data, assumptions, and results throughout the process.
- Gather and use large datasets from multiple sources across global marketplaces to design production-ready solutions that meet customer needs and team goals.
- Write accurate, clear, and mathematically rigorous technical documents that communicate model performance and business impact to both technical and non-technical audiences.
- Partner with engineering, business, and science teams to translate payment-domain problems into data science solutions and ensure smooth deployment on AWS.
A day in the life
You will spend your morning reviewing model outputs from production FX risk systems and tuning generative AI prototypes for seller chatbots. In the afternoon you might pair with an engineer to deploy a new model version on AWS, then present preliminary results to senior leadership. Throughout, you will seek feedback from senior scientists on your methodology and collaborate with cross-functional partners to refine problem framing.
About the team
We are the science team behind Amazon's cross-border payments business, supporting products that serve millions of sellers and buyers across 20+ global marketplaces. Our team is small and at an inflection point—we are expanding our generative AI capabilities, building multi-agent systems, and strengthening real-time risk models. You will join a group that values end-to-end ownership, from research to production, and whose work directly shapes decisions on large-scale payment flows.
BASIC QUALIFICATIONS
- 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
PREFERRED QUALIFICATIONS
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
- Experience working with or evaluating AI systems
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, WA, Seattle
COMPENSATION
- Salary Range: $108,300.00 - $160,000.00 USD annually
DESCRIPTION
Want to apply data science to one of Amazon's fastest-growing payment businesses, serving millions of sellers and buyers across 20+ global marketplaces? As a Data Scientist I on the cross-border payments science team, you will build and deploy production models that power real-time FX risk monitoring, generative AI seller chatbots, and multi-agent AI tools. You will work end-to-end—from problem framing through production deployment on AWS—delivering solutions that directly influence billion-dollar payment flows. This is a high-visibility, small-team environment where your work informs senior leadership decisions and creates measurable impact for customers worldwide.
Key job responsibilities
- Build, tune, and evaluate large language models and generative AI applications, including seller-facing chatbots and multi-agent AI tools for the cross-border payments business.
- Develop and deploy real-time statistical and machine learning models for FX risk monitoring, validating your data, assumptions, and results throughout the process.
- Gather and use large datasets from multiple sources across global marketplaces to design production-ready solutions that meet customer needs and team goals.
- Write accurate, clear, and mathematically rigorous technical documents that communicate model performance and business impact to both technical and non-technical audiences.
- Partner with engineering, business, and science teams to translate payment-domain problems into data science solutions and ensure smooth deployment on AWS.
A day in the life
You will spend your morning reviewing model outputs from production FX risk systems and tuning generative AI prototypes for seller chatbots. In the afternoon you might pair with an engineer to deploy a new model version on AWS, then present preliminary results to senior leadership. Throughout, you will seek feedback from senior scientists on your methodology and collaborate with cross-functional partners to refine problem framing.
About the team
We are the science team behind Amazon's cross-border payments business, supporting products that serve millions of sellers and buyers across 20+ global marketplaces. Our team is small and at an inflection point—we are expanding our generative AI capabilities, building multi-agent systems, and strengthening real-time risk models. You will join a group that values end-to-end ownership, from research to production, and whose work directly shapes decisions on large-scale payment flows.
BASIC QUALIFICATIONS
- 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
PREFERRED QUALIFICATIONS
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
- Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
- Experience working with or evaluating AI systems
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
- Experience effectively communicating complex concepts through written and verbal communication
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
LOCATION
USA, WA, Seattle
COMPENSATION
- Salary Range: $108,300.00 - $160,000.00 USD annually
Data Engineer Job Roles in Washington
See all 204+ Data Engineer Jobs in Washington
Sign up for free to filter by visa type, set job alerts, and find employers with verified sponsorship history.
Search Data Engineer Jobs in WashingtonData Engineer Jobs in Washington: Frequently Asked Questions
Which companies sponsor visas for data engineers in Washington?
Microsoft, Amazon, and Meta are among the most active sponsors for data engineer roles in Washington, with consistent H-1B visa filings visible in Department of Labor disclosure data. Mid-sized technology companies in the Seattle area, including Tableau, Zillow, and Expedia, also sponsor data engineers regularly. Consulting firms and cloud services vendors with Washington offices round out the sponsorship pool beyond the largest names.
Which visa types are most common for data engineer roles in Washington?
The H-1B is by far the most common visa category for data engineers in Washington, given that the role typically requires a bachelor's degree or higher in computer science, information systems, or a related field and meets the specialty occupation standard. Candidates already in the U.S. on F-1 OPT, including the 24-month STEM extension available for qualifying degrees, frequently use that period to secure H-1B sponsorship through Washington employers.
Which cities in Washington have the most data engineer sponsorship jobs?
Seattle and its immediate suburbs, including Bellevue, Redmond, and Kirkland, account for the large majority of data engineer sponsorship jobs in Washington. Redmond is home to Microsoft's headquarters, while Amazon's offices are concentrated in Seattle proper. Smaller but growing pockets of tech hiring exist in the Eastside corridor. Outside the metro, data engineering opportunities with sponsorship are considerably more limited.
How to find data engineer visa sponsorship jobs in Washington?
Migrate Mate is built specifically for international candidates looking for visa sponsorship roles, including data engineer positions in Washington. The platform filters jobs by sponsorship willingness and state, so you're not sifting through listings that don't apply to your situation. Focusing your search on Seattle metro employers with documented H-1B filing histories, which Migrate Mate surfaces, significantly narrows the field to realistic opportunities.
Are there any state-specific factors data engineers should know when pursuing sponsorship in Washington?
Washington has no state income tax, which affects how total compensation is structured relative to other tech hubs. The University of Washington produces a significant pipeline of computer science and data-focused graduates, which means competition for entry-level sponsorship roles can be strong. Data engineers targeting Washington employers should expect prevailing wage requirements to reflect the Seattle metro's market rates, which the Department of Labor determines based on local surveys and are employer obligations under the H-1B Labor Condition Application.
What is the prevailing wage for sponsored data engineer jobs in Washington?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.