J-1 Visa Cloud Data Engineer Jobs
Cloud Data Engineer roles in the U.S. are accessible to exchange visitors through the J-1 Trainee or Research Scholar program category, depending on your career stage. Finding a host employer willing to work with a designated sponsor for J-1 sponsorship requires a focused, strategic search from day one.
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Get Access To All JobsWho we are:
Farm Credit Bank of Texas is a $38.9 billion wholesale bank that has been financing agriculture and rural America for over 100 years. Headquartered in Austin, Texas, we provide funding and services to rural lending associations in five states, and we are active in the nation’s capital markets.
While you may not be familiar with our name, Farm Credit Bank of Texas plays a critical role in supporting the businesses that make it possible for America to maintain access to an affordable and safe food supply, an industry which is one of the most innovative and evolving of our time. And while you help us deliver on our mission, we deliver on our commitment to you as a valued employee by providing competitive compensation, generous health and wellness benefits packages and an attractive hybrid workplace located along the bluffs of the Colorado River just minutes west of downtown Austin.
We seek out top talent in their fields, whether it be technology, finance, accounting, credit, human resources, or other administrative functions, and welcome you to join us in our mission to feed the world.
Position Description:
The Data Engineer Intern supports the enterprise Cloud Data Platform team, working under the guidance of the Director, Data Architecture & AI Toolkit. This role is designed for a Master’s-level Computer Science student seeking hands-on experience building, enhancing, and innovating small tools, utilities, and platform components across data engineering, analytics enablement, and ML/AI workflows.
The intern will contribute to production-adjacent engineering work, focusing on automation, platform utilities, data pipelines, quality checks, and AI-assisted tooling that improve developer productivity, data reliability, and platform efficiency.
Day-to Day-Duties and Responsibilities:
- Assist in the design and development of data pipelines, ingestion utilities, and transformation logic on cloud data platforms (Databricks, Azure, etc)
- Build small internal tools and utilities to support platform operations, developer experience, and governance automation
- Assist in implementing data quality scorecard framework covering data validation, reconciliation, and quality checks
- Experiment with AI-assisted tooling, such as metadata enrichment, data quality recommendations, or intelligent monitoring prototypes
- Collaborate with platform and analytics teams on proof-of-concepts involving ML or GenAI capabilities
- Support implementation of bronze / silver / gold style data processing patterns under senior engineer guidance
- Develop reusable scripts, libraries, and utilities to simplify common platform tasks
- Assist with automation for monitoring, validation, data quality checks, and operational reporting
- Contribute to CI/CD pipelines, configuration scripts, and deployment automation where applicable
- Support development of data preparation and feature engineering utilities for ML and AI use cases
- Gain exposure to data platform operations, including incident analysis, performance tuning, and cost optimization activities
- Help document testing approaches and quality metrics
- Create and maintain technical documentation, diagrams, and runbooks for tools and utilities developed
- Present work outcomes and learnings to the platform engineering team
Learning & Development Objectives:
- Develop hands-on experience with modern cloud data platforms
- Learn enterprise-grade data engineering, operational, and governance practices
- Gain exposure to real-world ML/AI enablement within a regulated, production environment
- Build a strong foundation for a future full-time data engineer or platform engineer role
What You Bring to the Team:
Our ideal candidate lives within a commutable distance from our office in Austin, Texas and willing to work onsite.
It is an important role that covers many skills. This position requires:
- Strong foundation in Python and SQL
- Familiarity with data engineering concepts such as ETL/ELT, data modeling, and batch & stream processing
- Exposure to cloud platforms (Databricks, Azure, AWS, or GCP) and modern data tools
- Detailed understanding of ML concepts such as feature engineering, training pipelines, or model inputs is a plus
- Experience using Git and collaborative development workflows
- Strong analytical and problem-solving skills
- Curiosity and willingness to learn complex data and platform concepts
- Ability to work independently on well-defined tasks while collaborating with senior engineers
- Ability to collaborate and excel in complex, cross-functional teams involving data engineers, business analysts, and stakeholders
- Clear written and verbal communication skills
- Attention to detail and quality-focused mindset
Education:
- Currently pursuing a Master’s degree in Computer Science, Data Science, Software Engineering, or related field
- OR recently completed a Master’s degree in Computer Science or a related field and eligible to work in the U.S. under Optional Practical Training (OPT)
Important note: We care about your hiring process and take it seriously. A real person will review your applications, meaning response timelines may vary. The interviewing process at Farm Credit Bank of Texas may include phone calls and emails, on-site interviews, and requests for portfolios or demonstrations of work. We cannot personally follow-up with each applicant, and we will do our best to create a professional, respectful, and thorough process for candidates with whom we identify as a potential fit.
A/EOE/M/F/D/V
LI-Onsite
Who we are:
Farm Credit Bank of Texas is a $38.9 billion wholesale bank that has been financing agriculture and rural America for over 100 years. Headquartered in Austin, Texas, we provide funding and services to rural lending associations in five states, and we are active in the nation’s capital markets.
While you may not be familiar with our name, Farm Credit Bank of Texas plays a critical role in supporting the businesses that make it possible for America to maintain access to an affordable and safe food supply, an industry which is one of the most innovative and evolving of our time. And while you help us deliver on our mission, we deliver on our commitment to you as a valued employee by providing competitive compensation, generous health and wellness benefits packages and an attractive hybrid workplace located along the bluffs of the Colorado River just minutes west of downtown Austin.
We seek out top talent in their fields, whether it be technology, finance, accounting, credit, human resources, or other administrative functions, and welcome you to join us in our mission to feed the world.
Position Description:
The Data Engineer Intern supports the enterprise Cloud Data Platform team, working under the guidance of the Director, Data Architecture & AI Toolkit. This role is designed for a Master’s-level Computer Science student seeking hands-on experience building, enhancing, and innovating small tools, utilities, and platform components across data engineering, analytics enablement, and ML/AI workflows.
The intern will contribute to production-adjacent engineering work, focusing on automation, platform utilities, data pipelines, quality checks, and AI-assisted tooling that improve developer productivity, data reliability, and platform efficiency.
Day-to Day-Duties and Responsibilities:
- Assist in the design and development of data pipelines, ingestion utilities, and transformation logic on cloud data platforms (Databricks, Azure, etc)
- Build small internal tools and utilities to support platform operations, developer experience, and governance automation
- Assist in implementing data quality scorecard framework covering data validation, reconciliation, and quality checks
- Experiment with AI-assisted tooling, such as metadata enrichment, data quality recommendations, or intelligent monitoring prototypes
- Collaborate with platform and analytics teams on proof-of-concepts involving ML or GenAI capabilities
- Support implementation of bronze / silver / gold style data processing patterns under senior engineer guidance
- Develop reusable scripts, libraries, and utilities to simplify common platform tasks
- Assist with automation for monitoring, validation, data quality checks, and operational reporting
- Contribute to CI/CD pipelines, configuration scripts, and deployment automation where applicable
- Support development of data preparation and feature engineering utilities for ML and AI use cases
- Gain exposure to data platform operations, including incident analysis, performance tuning, and cost optimization activities
- Help document testing approaches and quality metrics
- Create and maintain technical documentation, diagrams, and runbooks for tools and utilities developed
- Present work outcomes and learnings to the platform engineering team
Learning & Development Objectives:
- Develop hands-on experience with modern cloud data platforms
- Learn enterprise-grade data engineering, operational, and governance practices
- Gain exposure to real-world ML/AI enablement within a regulated, production environment
- Build a strong foundation for a future full-time data engineer or platform engineer role
What You Bring to the Team:
Our ideal candidate lives within a commutable distance from our office in Austin, Texas and willing to work onsite.
It is an important role that covers many skills. This position requires:
- Strong foundation in Python and SQL
- Familiarity with data engineering concepts such as ETL/ELT, data modeling, and batch & stream processing
- Exposure to cloud platforms (Databricks, Azure, AWS, or GCP) and modern data tools
- Detailed understanding of ML concepts such as feature engineering, training pipelines, or model inputs is a plus
- Experience using Git and collaborative development workflows
- Strong analytical and problem-solving skills
- Curiosity and willingness to learn complex data and platform concepts
- Ability to work independently on well-defined tasks while collaborating with senior engineers
- Ability to collaborate and excel in complex, cross-functional teams involving data engineers, business analysts, and stakeholders
- Clear written and verbal communication skills
- Attention to detail and quality-focused mindset
Education:
- Currently pursuing a Master’s degree in Computer Science, Data Science, Software Engineering, or related field
- OR recently completed a Master’s degree in Computer Science or a related field and eligible to work in the U.S. under Optional Practical Training (OPT)
Important note: We care about your hiring process and take it seriously. A real person will review your applications, meaning response timelines may vary. The interviewing process at Farm Credit Bank of Texas may include phone calls and emails, on-site interviews, and requests for portfolios or demonstrations of work. We cannot personally follow-up with each applicant, and we will do our best to create a professional, respectful, and thorough process for candidates with whom we identify as a potential fit.
A/EOE/M/F/D/V
LI-Onsite
See all 57+ Cloud Data Engineer jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Cloud Data Engineer roles.
Get Access To All JobsTips for Finding J-1 Visa Sponsorship as a Cloud Data Engineer
Align your credentials with specialty occupation standards
Before applying, confirm your degree and cloud engineering experience map to a recognized specialty field. Designated sponsors assess whether your background justifies a DS-2019 Training Plan, so gaps between your credentials and the posted role create delays.
Target host employers with prior J-1 hosting history
Search Migrate Mate to filter Cloud Data Engineer roles by employers that have previously hosted J-1 exchange visitors. Prior hosting history signals that a company already understands the DS-2019 process and won't withdraw when the sponsor relationship is explained.
Distinguish Trainee from Research Scholar in your outreach
Early-career professionals without a U.S. degree typically qualify under the Trainee category, while doctoral-level cloud researchers at universities or labs fit Research Scholar. Framing your category correctly in cover letters prevents employers from assuming you need H-1B sponsorship instead.
Verify the host employer qualifies under DOL standards
Your designated sponsor will confirm the host site meets DOL standards for supervised training before issuing a DS-2019. Employers without a structured onboarding program for the cloud engineering role you're filling will fail this review, so ask about training documentation early in interviews.
Request a draft Training Plan before accepting an offer
The DS-2019 Training/Internship Placement Plan must detail specific cloud engineering tasks, tools, and learning objectives by phase. Ask the host employer to draft this document alongside the offer letter so your designated sponsor can review it without causing start-date delays.
Check the 2-year home residency requirement early
Certain J-1 participants, particularly those funded by their home government or coming from countries on the Exchange Visitor Skills List, must return home for two years before changing to H-1B or green card status. USCIS and the State Department both assess this, so confirm your eligibility before signing.
Cloud Data Engineer jobs are hiring across the US. Find yours.
Find Cloud Data Engineer JobsCloud Data Engineer J-1 Visa: Frequently Asked Questions
Which J-1 program category fits a Cloud Data Engineer role?
It depends on your career stage. If you're a current student or within one year of graduation, the Intern category applies. If you've completed your degree and have relevant professional experience, the Trainee category is the standard fit. Doctoral-level engineers conducting cloud research at a university or national lab may qualify as a Research Scholar instead.
Who actually sponsors the J-1 visa for a Cloud Data Engineer?
The J-1 visa sponsor is a U.S. Department of State-designated organization, such as IIE, Cultural Vistas, or AIPT, not the hiring employer. The employer acts as a host site. The designated sponsor issues your DS-2019, reviews the Training Plan, and monitors compliance throughout your program. Some host employers have existing relationships with a sponsor org; others require you to arrange one.
How do I find host employers open to J-1 exchange visitors?
Use Migrate Mate to search Cloud Data Engineer roles filtered by employers that have a documented history of hosting exchange visitors. Many tech and data-focused companies are open to J-1 Trainees but don't advertise it prominently, so targeting employers with prior international hiring patterns significantly improves your response rate compared to cold applications.
Does the 2-year home residency requirement apply to cloud engineering J-1 participants?
It applies to some, not all. USCIS and the State Department assess this based on whether your home country appears on the Exchange Visitor Skills List and whether your program was government-funded. Cloud engineering is often listed as a needed skill in developing countries. Check your DS-2019 for a section 4 notation, which confirms whether the requirement applies to you specifically.
What makes a Cloud Data Engineer role eligible for J-1 Trainee status?
The role must provide structured, supervised training in cloud architecture, data pipeline engineering, or a related specialty that builds on your existing degree. It cannot be a standard employment position filled for operational purposes. Your designated sponsor will require a Training/Internship Placement Plan documenting specific skills, tools, and learning phases before issuing the DS-2019 for a Trainee program.
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