OPT Data Engineer Intern Jobs
Data Engineer Intern roles are among the most OPT-friendly positions in tech, with employers regularly filing H-1B visa sponsorship for strong interns. Most positions require Python, SQL, and familiarity with cloud platforms. STEM OPT extension eligibility makes this role a strong fit for a 3-year authorization window.
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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 114+ OPT Data Engineer Intern Jobs
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Get Access To All JobsTips for Finding OPT Sponsorship as a Data Engineer Intern
Target companies with active H-1B filing histories
Employers who regularly sponsor H-1B visas are far more likely to support OPT students through the full authorization period. Look for mid-size to large tech companies and consulting firms with established immigration infrastructure and dedicated HR teams.
Confirm STEM OPT eligibility before applying
Data Engineering typically qualifies for the 24-month STEM OPT extension, giving you up to three years of work authorization. Verify your degree CIP code is on the STEM designated degree program list before starting your job search.
Lead with your technical stack in applications
Employers screening OPT candidates want to see immediate technical contribution. Highlight proficiency in Python, SQL, Spark, and cloud platforms like AWS or GCP upfront. Concrete project experience with data pipelines reduces friction around work authorization conversations.
Start your OPT application at least 90 days early
USCIS allows you to apply up to 90 days before your program end date. Processing takes three to five months, so early filing protects your start date. Delays can push back internship offers, especially for structured summer programs with fixed timelines.
Ask about sponsorship intent during the offer stage
For internships with conversion potential, confirm whether the company sponsors H-1B visas before accepting. Asking late in the process wastes time for both sides. Frame it professionally: ask about their immigration support process for full-time conversion candidates.
Prioritize internships with full-time conversion pipelines
Internships that convert to full-time roles give you the best path through OPT and into H-1B sponsorship. Structured intern programs at established companies are more likely to have the legal and HR processes in place to support long-term work authorization.
Data Engineer Intern OPT: Frequently Asked Questions
Can I work as a Data Engineer Intern on OPT?
Yes. If your degree is in computer science, information systems, data science, or a related STEM field, Data Engineer Intern roles qualify for OPT work authorization. The position must be directly related to your major area of study. Most data engineering internships at tech and analytics companies meet this requirement, but confirm with your DSO before accepting an offer.
Does a Data Engineer Intern role qualify for the STEM OPT extension?
It can, provided two conditions are met: your degree program is on the STEM designated degree program list, and the employer is enrolled in E-Verify. Data engineering internships at most mid-size and large companies qualify. If approved, the extension adds 24 months to your initial 12-month OPT authorization, giving you up to three years total.
What happens if my Data Engineer Internship ends before my OPT period does?
OPT allows up to 90 days of unemployment during the standard 12-month period, and up to 150 days during the STEM extension. If your internship ends early, you have that window to find a new qualifying position. Use Migrate Mate to browse OPT-friendly data engineering roles and avoid burning through your unemployment days without an active search strategy.
Do Data Engineer Intern roles typically lead to H-1B sponsorship?
Many do, but it depends entirely on the employer. Large tech companies, consulting firms, and financial institutions with established immigration programs regularly convert strong interns to full-time sponsored employees. Smaller startups are less predictable. If long-term sponsorship is a priority, target employers with a track record of H-1B filings and ask about conversion pathways before accepting an offer.
How many hours per week can I work as a Data Engineer Intern on OPT?
During post-completion OPT, you must work at least 20 hours per week for the position to count as qualifying employment. Most full-time internships run 40 hours per week, which comfortably satisfies this requirement. Part-time arrangements are permitted, but hours below 20 per week do not count toward your OPT employment record and accumulate as unemployment days.