Green Card Data Infrastructure Engineer Jobs
Data Infrastructure Engineer roles qualify for green card sponsorship under EB-2 for advanced-degree professionals and EB-3 for skilled workers with a bachelor's degree. Employers file PERM labor certification with DOL before petitioning USCIS, making infrastructure-focused engineering one of the more consistently sponsored specializations in U.S. tech hiring.
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Get Access To All JobsINTRODUCTION
Imagine what you could do here. At Apple, we believe new insights have a way of becoming excellent products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish.
The people here at Apple don’t just build products - they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it.
Manufacturing Systems and Infrastructure (MSI) team is an engineering organization under the Product Operations org. MSI is responsible for the design, development, and maintenance of systems tools, services, and applications required to efficiently run manufacturing operations at scale across global factory sites.
As an AI Data & Infrastructure Engineer with the MSI team, you will own the end to end design, build, and operation of scalable AI data systems that power enterprise GenAI and Agentic AI capabilities. Your work spans core platform services, data pipeline development and infrastructure provisioning, enabling manufacturing workflow automation through Agents and Agent skills.
DESCRIPTION
Create robust, scalable architectures for systems that handle data orchestration for AI features
Design, build, and maintain scalable AI data platforms, services, and APIs that support and enable Agentic AI workflow development & automation.
Develop data ingestion, transformation, and publishing pipelines for structured, unstructured, and multimodal data.
Design and implement Retrieval-Augmented Generation (RAG) pipelines, embedding workflows, vector database integrations, and metadata services for enterprise AI applications.
Be able to quickly build an idea so you and the team can work with hands-on products. Then iterate on the best of those prototypes.
Build and integrate tools that help make complex AI systems observable, understandable and debuggable
Strong understanding of distributed systems, parallel computing, and performance optimization
Collaborate with AI/ML engineers, software engineers, product teams, and domain experts to define AI data requirements and deliver production-ready data solutions.
Optimize platform scalability, reliability, performance, security, and cost across cloud-native environments and Agentic systems.
Ability to clearly communicate complex technical problems and collaborate with partners to develop solutions
MINIMUM QUALIFICATIONS
Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
8+ Experience designing and building scalable data platforms and distributed systems.
Strong programming skills in Python and SQL, with proficiency in Java or Scala preferred.
Experience with Airflow, Kubeflow, or MLflow to build and orchestrate scalable AI data pipelines.
Experience building scalable batch and streaming data pipelines using Spark (PySpark), Kafka, Airflow, and Ray, with proficiency in Pandas and modern data lake/lakehouse architectures (e.g., Iceberg, Delta Lake).
Experience using modern development tools, including AI-assisted coding tools, while applying sound engineering judgment to review, validate, and improve generated code.
Knowledge of RAG architectures, embedding generation, vector databases, and AI data preparation for LLMs and agentic AI.
Experience with cloud platforms (AWS, Azure, or GCP), Kubernetes, Docker, CI/CD, and Infrastructure as Code.
Demonstrated ability to understand complex user workflows, translate them into practical technical solutions, and collaborate across teams to deliver measurable outcomes.
Excellent communication and collaboration skills, with the ability to translate technical concepts into clear, business focused insights.
PREFERRED QUALIFICATIONS
Experience with or a strong understanding of Generative AI, LLMs, Agentic Systems, or RAG (Retrieval-Augmented Generation) workflows.
Experience integrating LLMs into existing systems
Experience with API design, both for other engineers to use, but also for AI systems.
Experience working with manufacturing, operational, IoT, or industrial data platforms.
Demonstrated ability to lead technical initiatives and mentor engineers.
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
INTRODUCTION
Imagine what you could do here. At Apple, we believe new insights have a way of becoming excellent products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish.
The people here at Apple don’t just build products - they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it.
Manufacturing Systems and Infrastructure (MSI) team is an engineering organization under the Product Operations org. MSI is responsible for the design, development, and maintenance of systems tools, services, and applications required to efficiently run manufacturing operations at scale across global factory sites.
As an AI Data & Infrastructure Engineer with the MSI team, you will own the end to end design, build, and operation of scalable AI data systems that power enterprise GenAI and Agentic AI capabilities. Your work spans core platform services, data pipeline development and infrastructure provisioning, enabling manufacturing workflow automation through Agents and Agent skills.
DESCRIPTION
Create robust, scalable architectures for systems that handle data orchestration for AI features
Design, build, and maintain scalable AI data platforms, services, and APIs that support and enable Agentic AI workflow development & automation.
Develop data ingestion, transformation, and publishing pipelines for structured, unstructured, and multimodal data.
Design and implement Retrieval-Augmented Generation (RAG) pipelines, embedding workflows, vector database integrations, and metadata services for enterprise AI applications.
Be able to quickly build an idea so you and the team can work with hands-on products. Then iterate on the best of those prototypes.
Build and integrate tools that help make complex AI systems observable, understandable and debuggable
Strong understanding of distributed systems, parallel computing, and performance optimization
Collaborate with AI/ML engineers, software engineers, product teams, and domain experts to define AI data requirements and deliver production-ready data solutions.
Optimize platform scalability, reliability, performance, security, and cost across cloud-native environments and Agentic systems.
Ability to clearly communicate complex technical problems and collaborate with partners to develop solutions
MINIMUM QUALIFICATIONS
Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
8+ Experience designing and building scalable data platforms and distributed systems.
Strong programming skills in Python and SQL, with proficiency in Java or Scala preferred.
Experience with Airflow, Kubeflow, or MLflow to build and orchestrate scalable AI data pipelines.
Experience building scalable batch and streaming data pipelines using Spark (PySpark), Kafka, Airflow, and Ray, with proficiency in Pandas and modern data lake/lakehouse architectures (e.g., Iceberg, Delta Lake).
Experience using modern development tools, including AI-assisted coding tools, while applying sound engineering judgment to review, validate, and improve generated code.
Knowledge of RAG architectures, embedding generation, vector databases, and AI data preparation for LLMs and agentic AI.
Experience with cloud platforms (AWS, Azure, or GCP), Kubernetes, Docker, CI/CD, and Infrastructure as Code.
Demonstrated ability to understand complex user workflows, translate them into practical technical solutions, and collaborate across teams to deliver measurable outcomes.
Excellent communication and collaboration skills, with the ability to translate technical concepts into clear, business focused insights.
PREFERRED QUALIFICATIONS
Experience with or a strong understanding of Generative AI, LLMs, Agentic Systems, or RAG (Retrieval-Augmented Generation) workflows.
Experience integrating LLMs into existing systems
Experience with API design, both for other engineers to use, but also for AI systems.
Experience working with manufacturing, operational, IoT, or industrial data platforms.
Demonstrated ability to lead technical initiatives and mentor engineers.
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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Get Access To All JobsTips for Finding Green Card Sponsorship as a Data Infrastructure Engineer
Document your infrastructure specialization before applying
PERM requires the employer to define a specific job requirement, not a general engineering role. Organize proof of your specialization in distributed systems, cloud infrastructure, or data pipelines so employers can accurately define the position around your credentials.
Target employers with active PERM filing history
Search the DOL OFLC disclosure data for data engineering job titles to identify employers who have filed PERM for infrastructure roles before. Past filings signal an existing sponsorship process rather than one you'd have to build from scratch.
Use Migrate Mate to filter roles by sponsorship status
Search Migrate Mate specifically for Data Infrastructure Engineer roles with green card sponsorship indicated. Filtering by sponsorship history saves you from applying to companies that only sponsor H-1B visa and have no PERM infrastructure in place.
Clarify EB-2 versus EB-3 eligibility with your prospective employer
EB-2 requires the role to genuinely need an advanced degree or its equivalent. If your employer posts the position as requiring only a bachelor's degree, you'll likely be filed under EB-3, which affects your priority date and wait time depending on your country of birth.
Understand how PERM recruitment affects your start date
PERM requires DOL-supervised recruitment before filing, which typically adds several months before your I-140 petition can be submitted. Factor this into offer negotiations so your H-1B or other status remains valid throughout the entire PERM and I-140 stage.
Verify your employer uses E-Verify before accepting an offer
E-Verify enrollment is a practical indicator of immigration compliance infrastructure. Employers already enrolled are more likely to have established relationships with immigration counsel and an internal process for managing PERM timelines for technical roles like yours.
Green Card Data Infrastructure Engineer: Frequently Asked Questions
Do Data Infrastructure Engineer roles qualify for EB-2 or EB-3 green card sponsorship?
Both categories apply depending on how the employer defines the role. EB-2 applies when the position genuinely requires an advanced degree or equivalent specialized experience. EB-3 covers roles requiring a bachelor's degree. Most data infrastructure positions are filed under EB-2 at larger tech employers, but EB-3 filings are common at mid-size companies where job descriptions specify a four-year degree.
How does green card sponsorship differ from H-1B for this role?
H-1B is a temporary status with a three-year initial period and annual cap exposure at registration. Green card sponsorship through PERM and I-140 targets permanent residency with no renewal cycle once approved. The PERM process is longer, typically 18 to 36 months from start to I-485 filing, but it removes annual cap risk entirely and gives you status portability once your I-140 is approved and your priority date is current.
What does the PERM process look like specifically for a Data Infrastructure Engineer?
Your employer files a labor condition application with DOL, conducts supervised recruitment to confirm no qualified U.S. workers are available, and then submits the PERM application. For technical roles like data infrastructure, the job description must clearly define the minimum requirements, including specific infrastructure technologies, so the prevailing wage determination from the OFLC Wage Search accurately reflects your specialty area.
How can I find Data Infrastructure Engineer jobs that already sponsor green cards?
Use Migrate Mate to search specifically for Data Infrastructure Engineer roles filtered by employment-based green card sponsorship history. Targeting employers with confirmed PERM filing activity for similar titles is far more efficient than applying broadly and asking about sponsorship during the interview process, where many hiring managers don't have visibility into their own company's immigration policies.
Can I switch employers after my green card process has started?
Once your I-140 is approved and has been pending for 180 days or more, federal law allows you to port your priority date to a new employer in a same or similar occupational classification. Data infrastructure and data engineering roles generally fall under the same SOC code structure, but your new employer will need to file a new I-140 and confirm the role qualifies for portability before you change jobs.