Data Engineer Jobs for OPT Students
Data Engineer roles are among the most OPT-friendly positions in tech, with strong employer demand for F-1 students skilled in Python, SQL, and cloud platforms like AWS or Azure. Most roles qualify as STEM OPT extensions, giving you up to three years of authorized work without H-1B sponsorship.
See All Data Engineer JobsOverview
Showing 5 of 7,391+ Data Engineer jobs
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all 7,391+ Data Engineer jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Engineer roles.
Get Access To All JobsAbout Artisan
We're building AI employees. Not chatbots. Not copilots. Autonomous digital workers that do real jobs.
Our first, Ava, is an AI BDR used by hundreds of companies. She researches leads, writes and sends emails in a customer's voice, runs multi-step outbound sequences, manages her own deliverability infrastructure, self-optimizes over time, and handles objections and meeting booking. She's not a tool someone uses. She's a teammate.
We're a YC W24 company, have raised $35M+ from investors including Y Combinator, and are at $8M+ ARR. Right now we're building Ava 2.0, a step change in what an AI employee can do. The engineering problems are hard and the surface area is enormous.
Role overview
You'll be the first Data Engineer on the Artisan team! We're managing a database of hundreds of millions of leads and creating real-time intent signals which monitor data fields for those leads. You'll own everything data-related at Artisan.
- Design, build, and maintain scalable data pipelines that process and transform large volumes of structured and unstructured data
- Manage ingestion from third-party APIs, internal systems, and customer datasets
- Develop and maintain data models, data schemas, and storage systems optimized for ML and product performance
- Collaborate with ML engineers to prepare model-ready datasets, embeddings, feature stores, and evaluation data
- Implement data quality monitoring, validation, and observability
- Work closely with product engineers to support new features that rely on complex data flows
- Optimize systems for performance, cost, and reliability
- Contribute to early architecture decisions, infrastructure design, and best practices for data governance
- Build tooling that enables the entire team to access clean, well-structured data
Location: San Francisco, New York, or Remote USA
Team: Engineering
Reports to: CPTO, Sam Stallings
Who you are
- 3+ years of experience as a Data Engineer
- Proficiency in Python, SQL, and modern data tooling (dbt, Airflow, Dagster, or similar)
- Comfort working in fast, ambiguous environments
- Experience designing and operating ETL/ELT pipelines in production
- Experience with cloud platforms (AWS, GCP, or Azure)
- Familiarity with data lakes, warehouses, and vector databases
- Experience integrating APIs and working with semi-structured data (JSON, logs, event streams)
- Strong understanding of data modeling and optimization
- Bonus: experience supporting LLMs, embeddings, or ML training pipelines
- Bonus: startup experience
Interview process
1. Introductory chat with our recruiter
2. 1 hour technical interview with an engineer
3. 1 hour technical interview with an engineer
4. 30-minute interview with Sam, our CPTO
5. 15-minute culture and values interview with Jaspar, our CEO
Our culture and values
- Founder mindset. Everyone acts like an owner: take initiative, think big, challenge ideas, and push for 10× outcomes
- Obsessed with impact. We apply the 80/20 rule, kill sunk costs quickly, and focus on what actually moves the needle
- Customer-first, always. Every decision is made with the customer experience at the center
- High standards, every detail. Quality matters in everything we ship, from product and code to copy and design
- Clear, direct communication. We value candor, fast responses, and feedback
- Winning team energy. We bring positive vibes, low ego, zero drama, and genuinely enjoy building together
About Artisan
We're building AI employees. Not chatbots. Not copilots. Autonomous digital workers that do real jobs.
Our first, Ava, is an AI BDR used by hundreds of companies. She researches leads, writes and sends emails in a customer's voice, runs multi-step outbound sequences, manages her own deliverability infrastructure, self-optimizes over time, and handles objections and meeting booking. She's not a tool someone uses. She's a teammate.
We're a YC W24 company, have raised $35M+ from investors including Y Combinator, and are at $8M+ ARR. Right now we're building Ava 2.0, a step change in what an AI employee can do. The engineering problems are hard and the surface area is enormous.
Role overview
You'll be the first Data Engineer on the Artisan team! We're managing a database of hundreds of millions of leads and creating real-time intent signals which monitor data fields for those leads. You'll own everything data-related at Artisan.
- Design, build, and maintain scalable data pipelines that process and transform large volumes of structured and unstructured data
- Manage ingestion from third-party APIs, internal systems, and customer datasets
- Develop and maintain data models, data schemas, and storage systems optimized for ML and product performance
- Collaborate with ML engineers to prepare model-ready datasets, embeddings, feature stores, and evaluation data
- Implement data quality monitoring, validation, and observability
- Work closely with product engineers to support new features that rely on complex data flows
- Optimize systems for performance, cost, and reliability
- Contribute to early architecture decisions, infrastructure design, and best practices for data governance
- Build tooling that enables the entire team to access clean, well-structured data
Location: San Francisco, New York, or Remote USA
Team: Engineering
Reports to: CPTO, Sam Stallings
Who you are
- 3+ years of experience as a Data Engineer
- Proficiency in Python, SQL, and modern data tooling (dbt, Airflow, Dagster, or similar)
- Comfort working in fast, ambiguous environments
- Experience designing and operating ETL/ELT pipelines in production
- Experience with cloud platforms (AWS, GCP, or Azure)
- Familiarity with data lakes, warehouses, and vector databases
- Experience integrating APIs and working with semi-structured data (JSON, logs, event streams)
- Strong understanding of data modeling and optimization
- Bonus: experience supporting LLMs, embeddings, or ML training pipelines
- Bonus: startup experience
Interview process
1. Introductory chat with our recruiter
2. 1 hour technical interview with an engineer
3. 1 hour technical interview with an engineer
4. 30-minute interview with Sam, our CPTO
5. 15-minute culture and values interview with Jaspar, our CEO
Our culture and values
- Founder mindset. Everyone acts like an owner: take initiative, think big, challenge ideas, and push for 10× outcomes
- Obsessed with impact. We apply the 80/20 rule, kill sunk costs quickly, and focus on what actually moves the needle
- Customer-first, always. Every decision is made with the customer experience at the center
- High standards, every detail. Quality matters in everything we ship, from product and code to copy and design
- Clear, direct communication. We value candor, fast responses, and feedback
- Winning team energy. We bring positive vibes, low ego, zero drama, and genuinely enjoy building together
How to Get Visa Sponsorship as a Data Engineer
Build a portfolio around real data pipelines
Employers hiring data engineers want proof you can build and maintain production-grade pipelines. Publish GitHub projects showing ETL workflows, data modeling, or orchestration with tools like Airflow or dbt to demonstrate hands-on capability beyond coursework.
Emphasize cloud certifications to stand out
AWS Certified Data Engineer, Google Professional Data Engineer, or Azure Data Engineer certifications signal to hiring managers that you can contribute immediately. Certifications often offset concerns about sponsorship timelines by demonstrating high technical readiness.
Address OPT timing proactively with recruiters
Recruiters often assume OPT authorization is more complicated than it is. Prepare a one-sentence explanation of your current OPT status, remaining duration, and STEM extension eligibility so hiring conversations move forward without confusion or hesitation.
Apply to mid-size tech and data-driven companies
Startups and mid-size companies in fintech, healthtech, and SaaS often have urgent data engineering needs and more flexible hiring processes. They're frequently more willing to sponsor OPT workers than large enterprises with rigid HR policies.
Data Engineer jobs are hiring across the US. Find yours.
Find Data Engineer JobsSee all 7,391+ Data Engineer jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Engineer roles.
Get Access To All JobsFrequently Asked Questions
Does a Data Engineer role qualify for the STEM OPT extension?
Yes. Data Engineering falls under CIP codes recognized as STEM-eligible, which means most F-1 students graduating from a qualifying program in computer science, information systems, or a related field can apply for the 24-month STEM OPT extension. Your role must be directly related to your degree field, and your employer must enroll in E-Verify to support the extension.
How do I find Data Engineer jobs that explicitly support OPT work authorization?
Migrate Mate filters job listings specifically for OPT-eligible candidates, so you can browse Data Engineer roles from employers already open to F-1 work authorization without screening out irrelevant listings. This saves significant time compared to parsing general job postings that rarely specify sponsorship willingness upfront.
Can I work as a Data Engineer contractor or on a project basis during OPT?
OPT requires that your employment be directly related to your degree field, but it does not require a full-time permanent position. Contract and project-based data engineering roles can qualify, provided each engagement is substantive and field-related. Self-employment is permitted under OPT if you can demonstrate you are actively engaged in work related to your degree.
What happens to my OPT if my Data Engineer job ends before my authorization period expires?
F-1 OPT students are allowed up to 90 days of unemployment during the initial OPT period, and up to 150 days during the STEM OPT extension. If your data engineering role ends, you must actively pursue new employment in your field. Exceeding the unemployment limit puts your status at risk, so tracking your dates carefully from the day employment ends is critical.
Do Data Engineer employers need to do anything special to hire me on OPT?
For standard OPT, employers do not need to file any immigration petition or take formal action. You simply present your EAD card as proof of work authorization. For the STEM OPT extension, your employer must be enrolled in E-Verify and complete a formal training plan with your designated school official. Most established tech companies already meet this requirement.
See which Data Engineer employers are hiring and sponsoring visas right now.
Search Data Engineer Jobs