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 JobsThe Company:
Faraday Future (FF) is a California-based embodied artificial intelligence ecosystem company, leveraging the latest technologies and world's best talent to realize exciting new possibilities in mobility and robotics. We're producing user-centric, technology-first vehicles and robots to establish new paradigms in human-AI interaction. We're not just seeking to change how our cars and robots work – we're seeking to change the way we drive and interact with machines. At FF, we're creating something new, something connected, and something with a true global impact.
Your Role:
As a Data Engineer (Agent Systems) in the Developer Portal & Infrastructure Department, you will help build the data foundation for FF's EAI Developer Platform, Open Developer Platform, and agent-system capabilities across its robotics and vehicle businesses. You will work with AI agent, backend, platform, and security teams to support data pipelines, RAG knowledge infrastructure, developer portal analytics, platform telemetry, and data quality systems that power Developer Portal, SDK/API, Data Engine, DevOps & Toolchain, and Agent Skill Store experiences.
Responsibilities:
- Build and maintain batch and streaming data pipelines for developer platform data, including documentation, SDK/API metadata, developer activity, platform telemetry, system logs, feedback signals, and business events.
- Support RAG and agent knowledge systems by preparing, cleaning, chunking, embedding, indexing, and refreshing data from technical documents, API references, code repositories, and developer support content.
- Design and evolve schemas, data models, and storage patterns across relational databases, analytical stores, object storage, and vector retrieval systems.
- Create and maintain datasets for developer portal analytics, platform health monitoring, API usage analysis, Data Engine reporting, and open-source ecosystem insights.
- Validate data correctness, freshness, latency, and retrieval quality for production agent workflows and developer-facing platform features.
- Improve data quality and reliability through monitoring dashboards, validation checks, freshness alerts, lineage tracking, incident reviews, and operational runbooks.
- Follow security, privacy, and compliance practices for access control, retention, auditability, sensitive data handling, and PII protection.
Basic Qualifications:
- Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or a related technical field.
- 0–2 years of experience in data engineering, software engineering, platform engineering, or related areas; internships, research, open-source contributions, or strong academic projects count.
- Solid programming skills in Python and strong working knowledge of SQL.
- Basic experience with at least one data processing or orchestration tool, such as Kafka, Spark, Flink, Airflow, Dagster, or dbt.
- Understanding of relational databases, schema design, joins, indexing, and query performance trade-offs.
- Familiarity with Linux, Git, Docker, and modern software development workflows.
- Interest in AI agents, RAG, developer platforms, open-source ecosystems, robotics, vehicles, or embodied intelligence.
Preferred Qualifications:
- Professional working proficiency in Mandarin Chinese and English.
- Exposure to analytical databases, warehouses, or storage systems such as ClickHouse, BigQuery, Snowflake, PostgreSQL, MySQL, Redis, S3, GCS, or Parquet.
- Familiarity with vector retrieval and RAG infrastructure, including embedding pipelines, metadata filtering, hybrid search, reindexing, pgvector, FAISS, Milvus, Weaviate, or Pinecone.
- Exposure to developer portals, SDK/API platforms, technical documentation platforms, DevOps toolchains, open-source communities, or Agent Skill Store-style ecosystems.
- Familiarity with Kubernetes, cloud infrastructure, CI/CD, observability, data lineage, cost monitoring, or production incident response.
- Basic understanding of privacy and compliance concepts such as GDPR, CCPA, data minimization, tokenization, pseudonymization, and role-based access control.
Annual Salary Range:
($85,000 - $95,000 DOE), plus benefits and incentive plans
Perks + Benefits
- Healthcare + dental + vision benefits (Free for you/discounted for family)
- 401(k) options
- Casual dress code + relaxed work environment
- Culturally diverse, progressive atmosphere
Faraday Future is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
The Company:
Faraday Future (FF) is a California-based embodied artificial intelligence ecosystem company, leveraging the latest technologies and world's best talent to realize exciting new possibilities in mobility and robotics. We're producing user-centric, technology-first vehicles and robots to establish new paradigms in human-AI interaction. We're not just seeking to change how our cars and robots work – we're seeking to change the way we drive and interact with machines. At FF, we're creating something new, something connected, and something with a true global impact.
Your Role:
As a Data Engineer (Agent Systems) in the Developer Portal & Infrastructure Department, you will help build the data foundation for FF's EAI Developer Platform, Open Developer Platform, and agent-system capabilities across its robotics and vehicle businesses. You will work with AI agent, backend, platform, and security teams to support data pipelines, RAG knowledge infrastructure, developer portal analytics, platform telemetry, and data quality systems that power Developer Portal, SDK/API, Data Engine, DevOps & Toolchain, and Agent Skill Store experiences.
Responsibilities:
- Build and maintain batch and streaming data pipelines for developer platform data, including documentation, SDK/API metadata, developer activity, platform telemetry, system logs, feedback signals, and business events.
- Support RAG and agent knowledge systems by preparing, cleaning, chunking, embedding, indexing, and refreshing data from technical documents, API references, code repositories, and developer support content.
- Design and evolve schemas, data models, and storage patterns across relational databases, analytical stores, object storage, and vector retrieval systems.
- Create and maintain datasets for developer portal analytics, platform health monitoring, API usage analysis, Data Engine reporting, and open-source ecosystem insights.
- Validate data correctness, freshness, latency, and retrieval quality for production agent workflows and developer-facing platform features.
- Improve data quality and reliability through monitoring dashboards, validation checks, freshness alerts, lineage tracking, incident reviews, and operational runbooks.
- Follow security, privacy, and compliance practices for access control, retention, auditability, sensitive data handling, and PII protection.
Basic Qualifications:
- Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or a related technical field.
- 0–2 years of experience in data engineering, software engineering, platform engineering, or related areas; internships, research, open-source contributions, or strong academic projects count.
- Solid programming skills in Python and strong working knowledge of SQL.
- Basic experience with at least one data processing or orchestration tool, such as Kafka, Spark, Flink, Airflow, Dagster, or dbt.
- Understanding of relational databases, schema design, joins, indexing, and query performance trade-offs.
- Familiarity with Linux, Git, Docker, and modern software development workflows.
- Interest in AI agents, RAG, developer platforms, open-source ecosystems, robotics, vehicles, or embodied intelligence.
Preferred Qualifications:
- Professional working proficiency in Mandarin Chinese and English.
- Exposure to analytical databases, warehouses, or storage systems such as ClickHouse, BigQuery, Snowflake, PostgreSQL, MySQL, Redis, S3, GCS, or Parquet.
- Familiarity with vector retrieval and RAG infrastructure, including embedding pipelines, metadata filtering, hybrid search, reindexing, pgvector, FAISS, Milvus, Weaviate, or Pinecone.
- Exposure to developer portals, SDK/API platforms, technical documentation platforms, DevOps toolchains, open-source communities, or Agent Skill Store-style ecosystems.
- Familiarity with Kubernetes, cloud infrastructure, CI/CD, observability, data lineage, cost monitoring, or production incident response.
- Basic understanding of privacy and compliance concepts such as GDPR, CCPA, data minimization, tokenization, pseudonymization, and role-based access control.
Annual Salary Range:
($85,000 - $95,000 DOE), plus benefits and incentive plans
Perks + Benefits
- Healthcare + dental + vision benefits (Free for you/discounted for family)
- 401(k) options
- Casual dress code + relaxed work environment
- Culturally diverse, progressive atmosphere
Faraday Future is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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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.