H-1B Visa Data Science Engineer Jobs
Data Science Engineer roles sit squarely within H-1B specialty occupation requirements, combining statistical modeling, machine learning, and software engineering under a single job title. Most sponsors file in the April lottery window, though cap-exempt employers at universities and nonprofits hire year-round. Your degree field and job duties must align for the LCA to hold.
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Get Access To All JobsINTRODUCTION
Adobe Customer Solutions is hiring a Senior Data Science Engineer to build practical AI and data systems for Adobe’s Digital Experience business.
This role focuses on the infrastructure behind GenAI agents, customer intelligence products, and field productivity workflows. The work includes data pipelines, Databricks workflows, LLM-powered agents, reusable platform services, and systems that help teams understand customer health, retention, growth, adoption, and value.
This is a hands-on engineering role. The team needs someone who can take an unclear business problem, shape the technical approach, build the data foundation, and ship reliable AI-enabled workflows into production. It is a great opportunity for someone who likes building systems that people use every day!
ROLE AND RESPONSIBILITIES
In this role, you’ll build and operate data and AI infrastructure used by Customer Success, Customer Engineering, Professional Services, and go-to-market teams. You will:
- Build production data pipelines, feature workflows, and platform services using Python, SQL, Spark, Databricks, Delta Lake, APIs, and cloud tools.
- Create LLM-powered agents and AI workflows that summarize customer signals, generate insights, recommend actions, and reduce manual work.
- Own platform components such as data ingestion, orchestration, semantic layers, tool integrations, access patterns, monitoring, and reliability.
- Combine structured and unstructured data from usage, adoption, support, success, value, account, and operational systems.
- Improve GenAI quality through evaluation, retrieval design, prompt and tool design, feedback loops, and production monitoring.
- Strengthen data quality, lineage, alerting, access control, governance, and operational support.
- Partner with product, engineering, data science, business operations, and customer-facing teams to turn priority problems into working systems.
- Apply strong engineering practices through Git, code review, CI/CD, Databricks Repos, documentation, and reproducible development.
A few questions this role will help answer:
Which customer signals matter most? Where can AI remove repetitive work? How should agents connect to trusted data? What platform capability would help multiple teams move faster?
WHAT YOU NEED TO SUCCEED
Strong candidates bring data engineering depth, GenAI fluency, platform thinking, and strong delivery judgment. Required qualifications:
- 8+ years in data engineering, machine learning engineering, data science engineering, analytics engineering, platform engineering, or a related technical role.
- Production work with Python, SQL, Spark, Databricks, Delta Lake, distributed data processing, and workflow orchestration.
- Hands-on work with GenAI or LLM systems, including agents, copilots, retrieval-augmented generation, semantic search, tool/function calling, prompt workflows, or AI automation.
- Strong knowledge of data modeling, data quality, lineage, access control, observability, and scalable pipeline design.
- Ability to guide work from discovery through architecture, development, deployment, monitoring, adoption, and iteration.
- Good judgment on when to prototype, when to harden for production, and how to manage technical debt.
- Clear communication with technical teams, business stakeholders, and senior leaders.
- Ability to work independently, navigate ambiguity, prioritize high-impact work, and deliver in a fast-moving environment.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related field, or equivalent practical experience.
PREFERRED QUALIFICATIONS
Helpful additional experience includes:
- Internal AI platforms, agent platforms, customer intelligence systems, or reusable data infrastructure.
- LLM evaluation, prompt evaluation, model monitoring, human feedback loops, AI governance, or responsible AI practices.
- Azure, AWS, or GCP, including secure deployment patterns and service integrations.
- Databricks Workflows, Airflow, Dagster, or similar orchestration tools.
- APIs, microservices, event-driven workflows, or application integrations.
- Vector databases, embeddings, semantic search, knowledge graphs, graph databases, Elastic Stack, Kafka, or Kinesis.
- Customer health, retention, adoption, growth, value realization, or enterprise SaaS operating models.
- Adobe Experience Cloud, Adobe Experience Platform, Adobe Analytics, Customer Journey Analytics, or related Digital Experience products.
WHAT SUCCESS LOOKS LIKE
In the first 90 days, this person will learn the core data and AI platform landscape, contribute to priority GenAI and data infrastructure work, and take ownership of meaningful production components.
Within six months, this person will own one or more foundation areas such as agent infrastructure, customer intelligence pipelines, orchestration, data quality, or reusable AI workflow services.
Over time, this role will help Adobe Customer Solutions move from individual AI prototypes to governed, production-grade systems that improve customer outcomes and field productivity across the business.
ABOUT ADOBE
Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity.
Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours.
Let’s Adobe together
At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture, focus on people, purpose and community, Adobe for All, comprehensive benefits programs, the stories we tell, the customers we serve, and how you can help us advance our mission of empowering everyone to create.
Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more.
Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call +1 408-536-3015.
AI USE GUIDELINES FOR INTERVIEWS:
Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.
At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience.
EXPECTED PAY RANGE: Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $133,100 - $236,400 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.
In California, the pay range for this position is $163,200 - $236,400
In New York, the pay range for this position is $163,200 - $236,400
In Illinois, the pay range for this position is $149,100 - $216,000
In Washington, the pay range for this position is $157,900 - $228,575
At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.
STATE-SPECIFIC NOTICES:
California:
Fair Chance Ordinances
Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.
Colorado:
Application Window Notice
If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs.
Massachusetts:
Massachusetts Legal Notice
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
INTRODUCTION
Adobe Customer Solutions is hiring a Senior Data Science Engineer to build practical AI and data systems for Adobe’s Digital Experience business.
This role focuses on the infrastructure behind GenAI agents, customer intelligence products, and field productivity workflows. The work includes data pipelines, Databricks workflows, LLM-powered agents, reusable platform services, and systems that help teams understand customer health, retention, growth, adoption, and value.
This is a hands-on engineering role. The team needs someone who can take an unclear business problem, shape the technical approach, build the data foundation, and ship reliable AI-enabled workflows into production. It is a great opportunity for someone who likes building systems that people use every day!
ROLE AND RESPONSIBILITIES
In this role, you’ll build and operate data and AI infrastructure used by Customer Success, Customer Engineering, Professional Services, and go-to-market teams. You will:
- Build production data pipelines, feature workflows, and platform services using Python, SQL, Spark, Databricks, Delta Lake, APIs, and cloud tools.
- Create LLM-powered agents and AI workflows that summarize customer signals, generate insights, recommend actions, and reduce manual work.
- Own platform components such as data ingestion, orchestration, semantic layers, tool integrations, access patterns, monitoring, and reliability.
- Combine structured and unstructured data from usage, adoption, support, success, value, account, and operational systems.
- Improve GenAI quality through evaluation, retrieval design, prompt and tool design, feedback loops, and production monitoring.
- Strengthen data quality, lineage, alerting, access control, governance, and operational support.
- Partner with product, engineering, data science, business operations, and customer-facing teams to turn priority problems into working systems.
- Apply strong engineering practices through Git, code review, CI/CD, Databricks Repos, documentation, and reproducible development.
A few questions this role will help answer:
Which customer signals matter most? Where can AI remove repetitive work? How should agents connect to trusted data? What platform capability would help multiple teams move faster?
WHAT YOU NEED TO SUCCEED
Strong candidates bring data engineering depth, GenAI fluency, platform thinking, and strong delivery judgment. Required qualifications:
- 8+ years in data engineering, machine learning engineering, data science engineering, analytics engineering, platform engineering, or a related technical role.
- Production work with Python, SQL, Spark, Databricks, Delta Lake, distributed data processing, and workflow orchestration.
- Hands-on work with GenAI or LLM systems, including agents, copilots, retrieval-augmented generation, semantic search, tool/function calling, prompt workflows, or AI automation.
- Strong knowledge of data modeling, data quality, lineage, access control, observability, and scalable pipeline design.
- Ability to guide work from discovery through architecture, development, deployment, monitoring, adoption, and iteration.
- Good judgment on when to prototype, when to harden for production, and how to manage technical debt.
- Clear communication with technical teams, business stakeholders, and senior leaders.
- Ability to work independently, navigate ambiguity, prioritize high-impact work, and deliver in a fast-moving environment.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related field, or equivalent practical experience.
PREFERRED QUALIFICATIONS
Helpful additional experience includes:
- Internal AI platforms, agent platforms, customer intelligence systems, or reusable data infrastructure.
- LLM evaluation, prompt evaluation, model monitoring, human feedback loops, AI governance, or responsible AI practices.
- Azure, AWS, or GCP, including secure deployment patterns and service integrations.
- Databricks Workflows, Airflow, Dagster, or similar orchestration tools.
- APIs, microservices, event-driven workflows, or application integrations.
- Vector databases, embeddings, semantic search, knowledge graphs, graph databases, Elastic Stack, Kafka, or Kinesis.
- Customer health, retention, adoption, growth, value realization, or enterprise SaaS operating models.
- Adobe Experience Cloud, Adobe Experience Platform, Adobe Analytics, Customer Journey Analytics, or related Digital Experience products.
WHAT SUCCESS LOOKS LIKE
In the first 90 days, this person will learn the core data and AI platform landscape, contribute to priority GenAI and data infrastructure work, and take ownership of meaningful production components.
Within six months, this person will own one or more foundation areas such as agent infrastructure, customer intelligence pipelines, orchestration, data quality, or reusable AI workflow services.
Over time, this role will help Adobe Customer Solutions move from individual AI prototypes to governed, production-grade systems that improve customer outcomes and field productivity across the business.
ABOUT ADOBE
Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity.
Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours.
Let’s Adobe together
At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture, focus on people, purpose and community, Adobe for All, comprehensive benefits programs, the stories we tell, the customers we serve, and how you can help us advance our mission of empowering everyone to create.
Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more.
Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call +1 408-536-3015.
AI USE GUIDELINES FOR INTERVIEWS:
Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.
At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience.
EXPECTED PAY RANGE: Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $133,100 - $236,400 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.
In California, the pay range for this position is $163,200 - $236,400
In New York, the pay range for this position is $163,200 - $236,400
In Illinois, the pay range for this position is $149,100 - $216,000
In Washington, the pay range for this position is $157,900 - $228,575
At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.
STATE-SPECIFIC NOTICES:
California:
Fair Chance Ordinances
Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.
Colorado:
Application Window Notice
If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs.
Massachusetts:
Massachusetts Legal Notice
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
See all 11,234+ Data Science Engineer jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Science Engineer roles.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as a Data Science Engineer
Align your degree to the role
USCIS scrutinizes whether your degree field directly relates to data science engineering duties. A degree in statistics, computer science, or applied mathematics strengthens your specialty occupation case. Unrelated degrees require detailed documentation showing how coursework maps to the role.
Check the LCA before accepting an offer
Your employer files a Labor Condition Application with DOL before submitting the I-129 petition. Verify the certified LCA lists the correct job title, worksite, and wage level so your H-1B petition matches the actual role you'll perform.
Target cap-exempt employers for year-round hiring
Universities, nonprofit research institutions, and government-affiliated organizations are exempt from the H-1B cap and annual lottery. Data science engineering roles at these employers can be sponsored any time of year, not only after the April registration window.
Use Migrate Mate to find active H-1B sponsors
Filter your job search by employers with verified H-1B LCA filing history for data science roles. Migrate Mate surfaces DOL disclosure data by occupation so you can target companies that have sponsored similar positions, not just those with general sponsorship policies.
Benchmark your wage against the OFLC prevailing level
DOL sets four wage levels for each SOC code and metro area. Data science engineering roles typically file at Level II or III. Use the OFLC Wage Search to confirm your offered salary meets or exceeds the prevailing wage for your specific location before the LCA is submitted.
Data Science Engineer jobs are hiring across the US. Find yours.
Find Data Science Engineer JobsData Science Engineer H-1B Visa: Frequently Asked Questions
Does a Data Science Engineer role qualify as a specialty occupation for H-1B purposes?
Yes, provided the position requires at least a bachelor's degree in a directly related field such as computer science, statistics, or data engineering. USCIS looks at whether a theoretical and practical application of a body of specialized knowledge is required. Job descriptions that mix generic software duties with data science responsibilities can trigger a Request for Evidence, so your employer's job description should clearly tie the role's core functions to a specific degree field.
What SOC code is typically used for Data Science Engineer H-1B petitions?
Employers most commonly file under SOC 15-2051 (Data Scientists) or 15-1243 (Database Architects), depending on how the role is defined. Some filings use 15-1252 (Software Developers) when the engineering component is dominant. The SOC code determines the prevailing wage level, so it directly affects the salary your employer must certify on the LCA. You can look up the occupation description and typical requirements on O*NET.
How do I find employers that actively sponsor H-1B visas for Data Science Engineer roles?
Search Migrate Mate to filter for employers with verified H-1B LCA filing history specifically for data science and engineering job titles. DOL publishes quarterly LCA disclosure data, and Migrate Mate maps that data to searchable employer profiles so you can see which companies have sponsored comparable roles rather than relying on self-reported sponsorship policies.
Can I change employers on H-1B if I get a better data science offer mid-status?
Yes. H-1B portability under AC21 lets you start working for a new employer as soon as they file a new I-129 petition on your behalf, as long as your current H-1B has been approved for at least 180 days and the new role is in the same or a similar occupational classification. Your new employer must file before your current H-1B expires to maintain continuous status.
Does working remotely for an H-1B-sponsored data science role create any compliance issues?
Yes. If you work from a location not listed on the certified LCA, your employer may need to file an amended I-129 petition and post the LCA notice at the new worksite. Remote work across multiple states or cities is a known compliance risk because each worksite's prevailing wage must be certified separately. Confirm with your employer's immigration counsel before changing your primary work location.
See which Data Science Engineer employers are hiring and sponsoring visas right now.
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