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 JobsJOB DESCRIPTION
Job Description: Data Infrastructure & ML Engineer (Hybrid Role)
Role Summary
We are seeking a Senior Data Infrastructure & Machine Learning Engineer to design and implement scalable data systems and pipelines that support advanced analytics and machine learning workflows.
This is a hybrid role where the primary focus is on data pipeline engineering and Python-based data processing, supported by strong database design and management expertise.
Role Focus (Approximate Split)
- Data Pipeline Engineering & Data Flow (Critical): ~50%
- Python & Machine Learning Data Processing: ~30%
- Database Design & Management: ~20%
Key Responsibilities
1. Data Pipeline Engineering (Primary Responsibility)
- Design and build end-to-end data pipelines (ETL/ELT) for ingesting, processing, and transforming data.
- Handle multiple data sources including:
- Tool-generated logs (e.g., AT log files)
- JSON and semi-structured data
- Ensure full data traceability, enabling backward tracking of all data points.
- Implement validation, monitoring, and error handling to ensure data quality and reliability.
2. Database Design & Data Architecture
- Design and manage scalable database schemas.
- Support both single-node and distributed database environments.
- Implement tablespaces, partitioning, and sharding strategies to ensure performance and scalability.
- Optimize queries and maintain high performance for large-scale datasets.
3. Python-Based Data Processing & Analytics
- Develop data processing workflows using Python.
- Work extensively with dataframes for transformation and analysis.
- Utilize libraries such as:
- Pandas, NumPy for data manipulation
- Plotly (or similar) for visualization and exploratory analysis
- Automate data workflows and integrate them into pipelines.
4. Machine Learning Data Enablement
- Prepare and transform datasets for machine learning models.
- Collaborate with data scientists and engineers to support model training and deployment workflows.
- Enable scalable data foundations for AI/ML integration into production systems.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field with 5+ years of experience.
- Strong experience in database design and SQL-based systems.
- Hands-on experience with distributed systems, partitioning, and sharding.
- Proven experience building data pipelines (ETL/ELT).
- Strong proficiency in Python for data processing.
- Experience working with log-based and semi-structured data (e.g., JSON).
- Understanding of data traceability, validation, and governance.
Preferred Qualifications
- Experience with time-series or log analytics systems.
- Exposure to real-time/streaming architectures (e.g., Kafka).
- Experience with cloud platforms (Azure, AWS, or GCP).
- Familiarity with machine learning workflows and lifecycle.
- Domain experience in semiconductor or high-throughput systems (nice to have).
Key Competencies
- Strong problem-solving and analytical skills.
- Ability to design production-grade, scalable systems.
- Focus on data integrity, performance, and reliability.
- Effective collaboration across engineering and data teams.
- Clear communication and documentation.
EQUAL OPPORTUNITY STATEMENT
It is the policy of Axcelis to provide equal opportunity in all areas of employment for all persons free from discrimination based on race, sex, religion, age, color, national origin, disability status, medical condition (including pregnancy), veteran status, sexual orientation, marital status, or any other characteristic protected by federal, state or local law. Axcelis will provide reasonable accommodation necessary to enable a disabled candidate or employee to perform the essential functions of the position, unless the accommodation would create an undue hardship for the Company.
U.S. BASE SALARY RANGE
$122,133.07 - $183,199.61
This base salary range reflects the typical compensation for this role across U.S. locations.
Our salary ranges are determined by role and level; individual pay is determined based on multiple factors, including job-related skills, experience, relevant education or training, work location, and internal equity. The range provides the opportunity for growth and progression as you develop within the role.
Base pay is one part of our U.S. total compensation package which includes eligibility in the Axcelis Team Incentive bonus plan, and comprehensive benefits package (for regular employees working 20+ hours a week).
JOB DESCRIPTION
Job Description: Data Infrastructure & ML Engineer (Hybrid Role)
Role Summary
We are seeking a Senior Data Infrastructure & Machine Learning Engineer to design and implement scalable data systems and pipelines that support advanced analytics and machine learning workflows.
This is a hybrid role where the primary focus is on data pipeline engineering and Python-based data processing, supported by strong database design and management expertise.
Role Focus (Approximate Split)
- Data Pipeline Engineering & Data Flow (Critical): ~50%
- Python & Machine Learning Data Processing: ~30%
- Database Design & Management: ~20%
Key Responsibilities
1. Data Pipeline Engineering (Primary Responsibility)
- Design and build end-to-end data pipelines (ETL/ELT) for ingesting, processing, and transforming data.
- Handle multiple data sources including:
- Tool-generated logs (e.g., AT log files)
- JSON and semi-structured data
- Ensure full data traceability, enabling backward tracking of all data points.
- Implement validation, monitoring, and error handling to ensure data quality and reliability.
2. Database Design & Data Architecture
- Design and manage scalable database schemas.
- Support both single-node and distributed database environments.
- Implement tablespaces, partitioning, and sharding strategies to ensure performance and scalability.
- Optimize queries and maintain high performance for large-scale datasets.
3. Python-Based Data Processing & Analytics
- Develop data processing workflows using Python.
- Work extensively with dataframes for transformation and analysis.
- Utilize libraries such as:
- Pandas, NumPy for data manipulation
- Plotly (or similar) for visualization and exploratory analysis
- Automate data workflows and integrate them into pipelines.
4. Machine Learning Data Enablement
- Prepare and transform datasets for machine learning models.
- Collaborate with data scientists and engineers to support model training and deployment workflows.
- Enable scalable data foundations for AI/ML integration into production systems.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field with 5+ years of experience.
- Strong experience in database design and SQL-based systems.
- Hands-on experience with distributed systems, partitioning, and sharding.
- Proven experience building data pipelines (ETL/ELT).
- Strong proficiency in Python for data processing.
- Experience working with log-based and semi-structured data (e.g., JSON).
- Understanding of data traceability, validation, and governance.
Preferred Qualifications
- Experience with time-series or log analytics systems.
- Exposure to real-time/streaming architectures (e.g., Kafka).
- Experience with cloud platforms (Azure, AWS, or GCP).
- Familiarity with machine learning workflows and lifecycle.
- Domain experience in semiconductor or high-throughput systems (nice to have).
Key Competencies
- Strong problem-solving and analytical skills.
- Ability to design production-grade, scalable systems.
- Focus on data integrity, performance, and reliability.
- Effective collaboration across engineering and data teams.
- Clear communication and documentation.
EQUAL OPPORTUNITY STATEMENT
It is the policy of Axcelis to provide equal opportunity in all areas of employment for all persons free from discrimination based on race, sex, religion, age, color, national origin, disability status, medical condition (including pregnancy), veteran status, sexual orientation, marital status, or any other characteristic protected by federal, state or local law. Axcelis will provide reasonable accommodation necessary to enable a disabled candidate or employee to perform the essential functions of the position, unless the accommodation would create an undue hardship for the Company.
U.S. BASE SALARY RANGE
$122,133.07 - $183,199.61
This base salary range reflects the typical compensation for this role across U.S. locations.
Our salary ranges are determined by role and level; individual pay is determined based on multiple factors, including job-related skills, experience, relevant education or training, work location, and internal equity. The range provides the opportunity for growth and progression as you develop within the role.
Base pay is one part of our U.S. total compensation package which includes eligibility in the Axcelis Team Incentive bonus plan, and comprehensive benefits package (for regular employees working 20+ hours a week).
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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.