STEM OPT Data Engineering Intern Jobs
Data Engineering Intern roles qualify for STEM OPT when your degree falls under an eligible CIP code in computer science, information technology, or a related STEM field. Your employer must be enrolled in E-Verify, and the 24-month extension gives you up to 36 months total to build hands-on pipeline and infrastructure experience while maintaining F-1 status.
Find STEM OPT Data Engineering Intern JobsOverview
Showing 5 of 914+ Data Engineering Intern jobs
See all 914+ Data Engineering Intern Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Engineering Intern roles.
Get Access To All JobsPosition Summary
The Buck Institute for Research on Aging is seeking a full-time Bioinformatics and Data Scientist or Postdoctoral Researcher to join a collaborative research team focused on aging, multi-omics, computational biology, and translational data science. This position offers a unique opportunity to work in an academic research environment with a close-knit, interdisciplinary team while collaborating with leading experts in aging biology, bioinformatics, clinical research, and computational science. The successful candidate will contribute to a five-year government-funded project focused on advancing computational and multi-omics approaches to better understand human aging, biological resilience, and healthspan. This role will support broader nationwide efforts to develop data-driven approaches that may ultimately improve how aging and age-related disease risk are measured, modeled, and addressed. The ideal candidate will have strong experience in bioinformatics, statistics, computational biology, human omics data analysis, and scientific communication. The position is well suited for an independent, highly motivated scientist who enjoys working across disciplines and contributing to both discovery-driven and translational research.
Key Responsibilities
2. Analyze, curate, and manage research data
- Perform bioinformatics and data science analyses. The successful candidate will analyze diverse biological and clinical datasets, including but not limited to:
- Proteomics
- Metabolomics
- Methylomics
- Survey data
- Integrative multi-omics datasets
- Human biological aging and omics-clock data
- Drug repurposing analyses
- Enrichment and pathway analyses
- Dimensionality reduction and clustering
- Classification methods, including random forests and support vector machines
- Neural network-based approaches
- Simple and multiple linear regression
- Parametric and non-parametric statistical analyses
Responsibilities will include:
- Curating, organizing, and preparing data for analysis and upload to central repositories
- Supporting data harmonization across projects, cohorts, and collaborators in accordance with data use agreements
- Reviewing and improving standard operating procedures for data transfer, quality control, and management
- Coordinating with internal and external teams to ensure timely collection, transfer, and analysis of data
- Attending project meetings and contributing to improvements in data workflows, systems, and documentation
- Ensuring data quality, reproducibility, and compliance with project requirements
3. Collaborate with scientific and administrative teams
The candidate will work closely with staff members, research scientists, computational biologists, principal investigators, and external collaborators. Responsibilities may include:
- Contributing to grant applications, progress reports, and scientific proposals
- Supporting manuscript preparation and journal article writing
- Creating publication-quality figures, tables, and data visualizations
- Presenting analyses and findings to interdisciplinary research teams
- Helping translate complex computational results into clear biological and scientific interpretations
Qualifications
Required Education and Experience
- Strong background in both human biology and bioinformatics
- PhD in Computational Biology, Bioinformatics, Data Science, Biostatistics, Systems Biology, Computer Science, or a related field
- Minimum of 2 years of professional experience in a biological, biomedical, or computational research environment
- Strong proficiency in R, Python, and Bash scripting
- Demonstrated experience analyzing biological or biomedical datasets
- Experience developing, implementing, and running bioinformatics workflows
Required Skills
- Strong analytical, mathematical, and creative problem-solving skills
- Excellent written and oral communication skills
- Ability to work both independently and collaboratively in a team-based research environment
- Strong organizational skills and attention to detail
- Ability to prioritize and execute multiple tasks across concurrent projects
- Experience with reproducible data analysis practices and documentation
- Ability to communicate technical results to both computational and non-computational audiences
- Interest in applying large language models, agentic AI, or related computational tools to biomedical research workflows
Preferred Qualifications
- Experience with FDA approval process
- Experience with building apps
Compensation And Benefits
- Salary range: $80,000–$85,000, commensurate with experience
- Full-time, onsite position
- Exciting, collaborative work environment at the forefront of aging research
- Opportunity to work with state-of-the-art technologies and interdisciplinary scientific teams
- Generous benefits package, including:
- Health insurance
- Paid parental leave
- Generous paid time off
- 401(k) with 5% employer match
- Work visa sponsorship available for qualified candidates
About The Buck Institute
Our success will ultimately change healthcare. At the Buck Institute for Research on Aging, we aim to end the threat of age-related diseases for this and future generations by bringing together the most capable and passionate scientists from a broad range of disciplines to identify and impede the ways in which we age. The Buck is an independent, nonprofit institution located in Marin County, California, with the goal of increasing human healthspan, or the healthy years of life. Globally recognized as a pioneer and leader in efforts to target aging — the number one risk factor for diseases including Alzheimer’s disease, Parkinson’s disease, cancer, macular degeneration, heart disease, and diabetes — the Buck seeks to help people live better longer. We are an equal opportunity employer and strive to create an atmosphere where diversity of identity, experience, and background are welcomed, valued, and supported. Candidates who contribute to this diversity are strongly encouraged to apply.
To Apply
Interested candidates should click the Apply button to complete the online application. Please upload both:
- Your CV
- A brief statement of research interests, including the names and contact information for three references
Position Summary
The Buck Institute for Research on Aging is seeking a full-time Bioinformatics and Data Scientist or Postdoctoral Researcher to join a collaborative research team focused on aging, multi-omics, computational biology, and translational data science. This position offers a unique opportunity to work in an academic research environment with a close-knit, interdisciplinary team while collaborating with leading experts in aging biology, bioinformatics, clinical research, and computational science. The successful candidate will contribute to a five-year government-funded project focused on advancing computational and multi-omics approaches to better understand human aging, biological resilience, and healthspan. This role will support broader nationwide efforts to develop data-driven approaches that may ultimately improve how aging and age-related disease risk are measured, modeled, and addressed. The ideal candidate will have strong experience in bioinformatics, statistics, computational biology, human omics data analysis, and scientific communication. The position is well suited for an independent, highly motivated scientist who enjoys working across disciplines and contributing to both discovery-driven and translational research.
Key Responsibilities
2. Analyze, curate, and manage research data
- Perform bioinformatics and data science analyses. The successful candidate will analyze diverse biological and clinical datasets, including but not limited to:
- Proteomics
- Metabolomics
- Methylomics
- Survey data
- Integrative multi-omics datasets
- Human biological aging and omics-clock data
- Drug repurposing analyses
- Enrichment and pathway analyses
- Dimensionality reduction and clustering
- Classification methods, including random forests and support vector machines
- Neural network-based approaches
- Simple and multiple linear regression
- Parametric and non-parametric statistical analyses
Responsibilities will include:
- Curating, organizing, and preparing data for analysis and upload to central repositories
- Supporting data harmonization across projects, cohorts, and collaborators in accordance with data use agreements
- Reviewing and improving standard operating procedures for data transfer, quality control, and management
- Coordinating with internal and external teams to ensure timely collection, transfer, and analysis of data
- Attending project meetings and contributing to improvements in data workflows, systems, and documentation
- Ensuring data quality, reproducibility, and compliance with project requirements
3. Collaborate with scientific and administrative teams
The candidate will work closely with staff members, research scientists, computational biologists, principal investigators, and external collaborators. Responsibilities may include:
- Contributing to grant applications, progress reports, and scientific proposals
- Supporting manuscript preparation and journal article writing
- Creating publication-quality figures, tables, and data visualizations
- Presenting analyses and findings to interdisciplinary research teams
- Helping translate complex computational results into clear biological and scientific interpretations
Qualifications
Required Education and Experience
- Strong background in both human biology and bioinformatics
- PhD in Computational Biology, Bioinformatics, Data Science, Biostatistics, Systems Biology, Computer Science, or a related field
- Minimum of 2 years of professional experience in a biological, biomedical, or computational research environment
- Strong proficiency in R, Python, and Bash scripting
- Demonstrated experience analyzing biological or biomedical datasets
- Experience developing, implementing, and running bioinformatics workflows
Required Skills
- Strong analytical, mathematical, and creative problem-solving skills
- Excellent written and oral communication skills
- Ability to work both independently and collaboratively in a team-based research environment
- Strong organizational skills and attention to detail
- Ability to prioritize and execute multiple tasks across concurrent projects
- Experience with reproducible data analysis practices and documentation
- Ability to communicate technical results to both computational and non-computational audiences
- Interest in applying large language models, agentic AI, or related computational tools to biomedical research workflows
Preferred Qualifications
- Experience with FDA approval process
- Experience with building apps
Compensation And Benefits
- Salary range: $80,000–$85,000, commensurate with experience
- Full-time, onsite position
- Exciting, collaborative work environment at the forefront of aging research
- Opportunity to work with state-of-the-art technologies and interdisciplinary scientific teams
- Generous benefits package, including:
- Health insurance
- Paid parental leave
- Generous paid time off
- 401(k) with 5% employer match
- Work visa sponsorship available for qualified candidates
About The Buck Institute
Our success will ultimately change healthcare. At the Buck Institute for Research on Aging, we aim to end the threat of age-related diseases for this and future generations by bringing together the most capable and passionate scientists from a broad range of disciplines to identify and impede the ways in which we age. The Buck is an independent, nonprofit institution located in Marin County, California, with the goal of increasing human healthspan, or the healthy years of life. Globally recognized as a pioneer and leader in efforts to target aging — the number one risk factor for diseases including Alzheimer’s disease, Parkinson’s disease, cancer, macular degeneration, heart disease, and diabetes — the Buck seeks to help people live better longer. We are an equal opportunity employer and strive to create an atmosphere where diversity of identity, experience, and background are welcomed, valued, and supported. Candidates who contribute to this diversity are strongly encouraged to apply.
To Apply
Interested candidates should click the Apply button to complete the online application. Please upload both:
- Your CV
- A brief statement of research interests, including the names and contact information for three references
See all 914+ STEM OPT Data Engineering Intern Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT Data Engineering Intern Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization as a Data Engineering Intern
Verify your CIP code before applying
Check that your degree's CIP code appears on the DHS STEM Designated Degree Program list. Data engineering roles most often align with computer science, information systems, or electrical engineering codes, and a mismatch disqualifies your extension before you even start.
Screen job postings for E-Verify enrollment
Before submitting any application, confirm the employer is enrolled in E-Verify through the official E-Verify employer search. Internship postings rarely flag this upfront, so checking early saves you from accepting an offer that can't support your STEM OPT extension.
Build a portfolio around data pipeline projects
Hiring managers for data engineering intern roles expect evidence of ETL workflow design, SQL query optimization, or cloud data stack experience. A public GitHub repository with documented pipeline projects gives recruiters a concrete reason to move you forward over candidates with identical coursework.
Request the I-983 training plan before your start date
Your employer must complete and sign the I-983 before your STEM OPT extension begins. Ask your hiring manager or HR contact to initiate the training plan during onboarding so your DSO can submit the I-20 update to USCIS without delays that could gap your work authorization.
Use Migrate Mate to find E-Verify employers hiring interns
Filter your data engineering intern search on Migrate Mate to surface employers already enrolled in E-Verify and with OPT hiring history. This cuts the time you'd otherwise spend manually researching sponsorship eligibility company by company across general job boards.
Align your application timeline with your OPT end date
File your STEM OPT extension application with USCIS no later than 90 days before your initial OPT EAD expires. For data engineering intern roles that convert to full-time, this timeline also affects cap-gap eligibility if your employer files an H-1B visa petition on your behalf.
Frequently Asked Questions
Does a data engineering intern role qualify for the STEM OPT extension?
Yes, if your degree is in an eligible STEM field such as computer science, information systems, or a related discipline with a qualifying CIP code on the DHS STEM Designated Degree Program list. The role itself must also provide practical training directly related to your degree. Your DSO confirms eligibility when you apply for the extension through USCIS.
How do I know if a data engineering intern employer is enrolled in E-Verify?
Use the official E-Verify employer search tool to look up any company before you accept an offer. E-Verify enrollment is a hard requirement for STEM OPT, and internship postings rarely disclose this information upfront. You can also browse Data Engineering Intern roles on Migrate Mate, which surfaces employers with verified OPT hiring history so you're not starting from scratch on each application.
What goes into the I-983 training plan for a data engineering internship?
The I-983 requires your employer to describe the specific learning objectives, supervision structure, and how the internship connects to your STEM degree. For data engineering roles, this typically includes goals around pipeline architecture, data modeling, or cloud infrastructure work. Your employer signs the plan, your DSO updates your I-20, and you must report any material changes to training within five business days.
What happens to my STEM OPT if my data engineering internship converts to a full-time role and my employer files an H-1B petition?
If your employer files an H-1B petition on your behalf before your OPT EAD expires and you're selected in the lottery, cap-gap protections allow you to keep working through September 30 of that fiscal year even if your EAD expires first. You must maintain valid F-1 status throughout this period, and your DSO should update your SEVIS record to reflect the cap-gap extension.
Which STEM degree fields make you eligible for the STEM OPT extension in a data engineering role?
Degrees in computer science, computer engineering, information technology, electrical engineering, mathematics, and statistics are among the most common qualifying fields for data engineering positions. The degree must appear under an eligible CIP code on the DHS STEM Designated Degree Program list. Check O*NET for the occupational classification tied to the data engineering intern role to confirm the degree-to-occupation alignment your DSO will review.