Data Engineer Jobs in USA with Visa Sponsorship
Data engineer roles carry strong sponsorship potential due to their technical depth in building and maintaining large-scale data pipelines, ETL systems, and cloud infrastructure. Employers view data engineers similarly to software engineers when evaluating sponsorship decisions, and proficiency in platforms like AWS, GCP, Snowflake, and Spark significantly strengthens candidacy. STEM degree holders benefit from the 36-month OPT extension while pursuing long-term H-1B visa sponsorship. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsOur Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Senior Data Engineer
Overview
We are seeking a Senior Data Engineer with expertise in Apache Spark, Apache Iceberg, Apache Airflow, and AWS to design and build the next generation of our finance data platform. You will own finance-focused data products while contributing to foundational platform capabilities and engineering standards that scale across the enterprise.
The ideal candidate is a hands-on engineer who thrives in modern Lakehouse architecture, large-scale pipeline development and analytical mindset.
Key Responsibilities
Data Products:
- Design, develop, and maintain data products
- Ensure data products meet quality, auditability, lineage, and compliance standards
Platform Engineering & Framework Development:
- Build reusable data engineering frameworks and accelerators used across multiple teams
- Develop standardized patterns for ingestion, transformation, orchestration, monitoring, and data quality
- Contribute to and promote engineering standards and best practices across the team for Spark, Iceberg, Airflow, and cloud-native engineering
- Drive adoption of self-service platform capabilities and common engineering standards
- Build and optimize Apache Iceberg-based lakehouse solutions for analytical and operational workloads
- Design and optimize distributed processing workloads to ensure performance, resiliency, scalability, and cost efficiency
- Design, implement, and support workflow orchestration solutions that manage dependencies, scheduling, monitoring, and recovery across complex data pipelines
- Integrate and transform data from multiple internal and external sources to create trusted, reusable, and business-ready datasets
- Design and maintain logical and physical data models that support scalable analytics, reporting, and data product development
- Apply data security and governance standards including access controls, encryption, data masking, regulatory compliance, and secure data lifecycle management
Cloud Engineering:
- Build cloud-native solutions on AWS - S3, EMR, Glue, Lambda, ECS/EKS, CloudWatch
- Implement CI/CD pipelines, automated testing, and Infrastructure-as-Code
All About You
- 4+ years of experience in data engineering, data platform development, or related technical roles
- Experience designing and implementing scalable data platforms and data products in enterprise environments
- Knowledge of data mesh or data product architectures in enterprise settings
- Deep hands-on experience with Apache Spark (PySpark) for large-scale data processing and pipeline development
- Deep hands-on experience with Apache Iceberg or similar open table formats
- Solid understanding of CI/CD pipelines, infrastructure-as-code and DevOps practices
- Experience with data governance, data quality frameworks, and metadata management tools
- Strong experience with AWS Cloud services, including services such as Amazon S3, EMR, Glue, Lambda, ECS/EKS, and CloudWatch for developing, deploying, and managing cloud-native data solutions
Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
- Abide by Mastercard’s security policies and practices
- Ensure the confidentiality and integrity of the information being accessed
- Report any suspected information security violation or breach
- Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines
In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.
Pay Ranges
Miami, Florida: $115,000 - $184,000 USD
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Senior Data Engineer
Overview
We are seeking a Senior Data Engineer with expertise in Apache Spark, Apache Iceberg, Apache Airflow, and AWS to design and build the next generation of our finance data platform. You will own finance-focused data products while contributing to foundational platform capabilities and engineering standards that scale across the enterprise.
The ideal candidate is a hands-on engineer who thrives in modern Lakehouse architecture, large-scale pipeline development and analytical mindset.
Key Responsibilities
Data Products:
- Design, develop, and maintain data products
- Ensure data products meet quality, auditability, lineage, and compliance standards
Platform Engineering & Framework Development:
- Build reusable data engineering frameworks and accelerators used across multiple teams
- Develop standardized patterns for ingestion, transformation, orchestration, monitoring, and data quality
- Contribute to and promote engineering standards and best practices across the team for Spark, Iceberg, Airflow, and cloud-native engineering
- Drive adoption of self-service platform capabilities and common engineering standards
- Build and optimize Apache Iceberg-based lakehouse solutions for analytical and operational workloads
- Design and optimize distributed processing workloads to ensure performance, resiliency, scalability, and cost efficiency
- Design, implement, and support workflow orchestration solutions that manage dependencies, scheduling, monitoring, and recovery across complex data pipelines
- Integrate and transform data from multiple internal and external sources to create trusted, reusable, and business-ready datasets
- Design and maintain logical and physical data models that support scalable analytics, reporting, and data product development
- Apply data security and governance standards including access controls, encryption, data masking, regulatory compliance, and secure data lifecycle management
Cloud Engineering:
- Build cloud-native solutions on AWS - S3, EMR, Glue, Lambda, ECS/EKS, CloudWatch
- Implement CI/CD pipelines, automated testing, and Infrastructure-as-Code
All About You
- 4+ years of experience in data engineering, data platform development, or related technical roles
- Experience designing and implementing scalable data platforms and data products in enterprise environments
- Knowledge of data mesh or data product architectures in enterprise settings
- Deep hands-on experience with Apache Spark (PySpark) for large-scale data processing and pipeline development
- Deep hands-on experience with Apache Iceberg or similar open table formats
- Solid understanding of CI/CD pipelines, infrastructure-as-code and DevOps practices
- Experience with data governance, data quality frameworks, and metadata management tools
- Strong experience with AWS Cloud services, including services such as Amazon S3, EMR, Glue, Lambda, ECS/EKS, and CloudWatch for developing, deploying, and managing cloud-native data solutions
Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
- Abide by Mastercard’s security policies and practices
- Ensure the confidentiality and integrity of the information being accessed
- Report any suspected information security violation or breach
- Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines
In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.
Pay Ranges
Miami, Florida: $115,000 - $184,000 USD
See all 2,885+ 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 JobsTips for Finding Visa Sponsorship as a Data Engineer
Leverage data engineering's strong specialty occupation fit
Data engineering roles require deep knowledge of distributed systems, database architecture, and programming - a clear match for H-1B specialty occupation requirements. Job descriptions for this role rarely face the ambiguity challenges that more general analyst titles do.
Earn cloud data platform certifications
Snowflake SnowPro Core, Databricks Certified Data Engineer, and AWS Data Analytics Specialty certifications validate your expertise. They signal to employers that you can hit the ground running on their data stack.
Target companies building modern data platforms
Every company with significant data needs pipeline engineers. Snowflake, Databricks, dbt Labs, and Confluent are building the data tools themselves and sponsor H-1B petitions for engineers who understand the technology deeply.
Use STEM OPT to master your company's data stack
A STEM-eligible degree gives you up to 3 years of work authorization through OPT. Data pipelines are complex and company-specific - employers are more likely to sponsor someone who already knows their Airflow DAGs and Spark jobs.
Highlight the engineering depth of your role
Data engineering sits firmly on the software engineering side of the data spectrum. Emphasize skills in Spark, Airflow, dbt, and cloud infrastructure to distinguish your role from more general data positions when filing under SOC 15-1252.
Explore cap-exempt data infrastructure roles
University research computing teams and national labs process massive datasets and need data engineers to build the pipelines. These positions are H-1B cap-exempt - no lottery required and filing is open year-round.
Frequently Asked Questions
Is it easier to get visa sponsorship as a data engineer compared to a data scientist?
Data engineers and data scientists have comparable sponsorship strength, but the pathways differ slightly. Data engineer roles are closer to software engineering in scope, which gives them strong specialty occupation standing with USCIS. Data scientist roles often require advanced degrees, which provides an advantage through the H-1B visa master's cap exemption. Both are highly sponsorable, but data engineers may have an edge at companies with larger infrastructure needs.
Do cloud certifications like AWS or GCP help with H-1B approval for data engineers?
Cloud certifications do not directly affect H-1B approval, as the visa requires a bachelor's degree rather than certifications. However, they strengthen the overall petition by providing additional evidence that the role demands specialized technical knowledge. They also make you more competitive in the hiring process, which indirectly improves sponsorship chances by demonstrating alignment between your skills and the position's requirements.
Which industries sponsor data engineers most actively?
Technology companies are the largest sponsors, but financial services, healthcare, and e-commerce are close behind. Any company investing heavily in real-time analytics, data lakes, or ML infrastructure needs data engineers to build and maintain that foundation. Fintech companies and large banks are particularly active sponsors because their data pipelines are business-critical and require specialized expertise in distributed systems and regulatory data handling.
Do data engineers need a computer science degree specifically for visa sponsorship?
A computer science degree is the most common path, but degrees in information systems, software engineering, mathematics, or electrical engineering also qualify. The key is that the employer's job description lists your degree field among the qualifying fields for the position. USCIS evaluates whether your specific degree relates to the job duties, so a degree in statistics or applied math combined with strong technical experience in data pipeline development can work well.
How to find Data Engineer jobs with visa sponsorship?
To find Data Engineer jobs with visa sponsorship, use Migrate Mate, which specializes in connecting international talent with sponsoring employers. Focus on tech companies, financial institutions, and healthcare organizations that commonly sponsor H-1B, O-1 visa, and TN visas for data professionals. These industries actively recruit Data Engineers and have established visa sponsorship programs to secure skilled talent.
What technical skills should I highlight in a data engineer visa petition?
Proficiency in SQL, Python, and distributed computing frameworks like Spark or Kafka are foundational. Experience with cloud data platforms (AWS Redshift, Google BigQuery, Snowflake) and data orchestration tools (Airflow, dbt, Dagster) demonstrates the specialized technical depth USCIS looks for. Listing these specific technologies in the petition documentation helps distinguish the role from general software development and strengthens the specialty occupation case.
What is the prevailing wage requirement for sponsored Data Engineer jobs?
When a U.S. employer sponsors a foreign worker for a work visa, they are legally required to pay at least the "prevailing wage", the average wage paid to workers in the same occupation, in the same geographic area, with similar experience. This is set by the Department of Labor to prevent employers from hiring foreign workers at below-market rates. The prevailing wage varies significantly by role, location, and experience level. For example, a data engineer in California will have a different prevailing wage than the same role in a smaller state. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search Page.