AI Data Engineer Visa Sponsorship Jobs in New York
AI data engineer visa sponsorship jobs in New York are concentrated in Manhattan's finance and tech corridors, with major employers including JPMorgan Chase, IBM, Bloomberg, and Google's New York office. The state's dense cluster of financial institutions, media companies, and AI-focused startups makes it one of the most active hiring markets in the country for this role.
Find AI Data Engineer JobsOverview
Showing 5 of 549+ AI Data Engineer Jobs in New York with Visa Sponsorship
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 549+ AI Data Engineer Jobs in New York with Visa Sponsorship
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Data Engineer Jobs in New York with Visa Sponsorship.
Get Access To All JobsAbout The Role
Schonfeld Strategic Advisors is seeking an experienced AI Data Engineer to join our Data Engineering team. In this role, you will be responsible for designing, building, and maintaining robust data pipelines that power SchonAI, our firm's internal AI platform. You will work at the intersection of data engineering and AI, ensuring that high-quality, timely, and relevant data flows seamlessly to our AI systems to support investment professionals across the firm.
Key Responsibilities
Data Pipeline Development
- Design and build scalable, reliable data pipelines to ingest, transform, and deliver structured and unstructured data to SchonAI using Prefect.
- Develop ETL/ELT processes for diverse data sources including market data, research documents, internal databases, and third-party APIs.
- Implement real-time and batch data processing workflows to meet varying latency requirements.
- Ensure data quality, consistency, and integrity across all pipelines.
AI Data Infrastructure
- Build and maintain data infrastructure optimized for AI/ML workloads, including vector databases and semantic search systems.
- Design data schemas and storage solutions that support efficient retrieval and processing for LLM applications.
- Implement data versioning, lineage tracking, and observability for AI training and inference pipelines.
- Optimize data delivery for low-latency AI interactions and high-throughput batch processing.
Integration & Collaboration
- Partner with AI engineers, software developers, and data scientists to understand data requirements.
- Integrate with existing firm systems including risk platforms, trading systems, portfolio management tools, and research databases.
- Collaborate with infrastructure teams on cloud architecture, security, and compliance requirements.
- Work closely with business stakeholders to prioritize data sources and pipeline enhancements.
Data Governance & Security
- Implement appropriate data access controls, encryption, and compliance measures.
- Ensure adherence to data governance policies and regulatory requirements.
- Monitor and maintain data pipeline performance, reliability, and cost efficiency.
- Document data flows, transformations, and dependencies.
Required Qualifications
Technical Skills
- Programming: Strong proficiency in Python; experience with SQL and at least one other language (e.g. Java, Scala, Go, Rust)
- Data Engineering: 5+ years of experience building production data pipelines using tools like Apache Airflow, Prefect, Dagster, or similar
- Big Data Technologies: Hands-on experience with distributed computing frameworks (Spark, Flink) and modern data platforms
- Cloud Platforms: Proficiency with AWS services (S3, Kubernetes) or equivalent GCP services
- Databases: Experience with both SQL (PostgreSQL, MySQL) and NoSQL databases (MongoDB, DynamoDB, Elasticsearch)
- AI/ML Data: Understanding of data requirements for ML/AI systems, including experience with vector databases (Pinecone, Weaviate, Qdrant) and embedding pipelines
Preferred Experience
- Experience building data pipelines for LLM applications or RAG (Retrieval Augmented Generation) systems
- Familiarity with financial data sources (market data, fundamental data, alternative data)
- Knowledge of data streaming technologies (Kafka, Kinesis, Pub/Sub)
- Experience of Analytics/Warehouse/OLAP DB (BigQ, SingleStore, RedShift, ClickHouse)
- Experience with containerization (Docker) and orchestration (Kubernetes)
- Understanding of MLOps practices and tools
- Experience with data quality frameworks (Great Expectations, Deequ)
Professional Skills
- Bachelor's or Master's degree in Computer Science, Data Engineering, or related technical field
- Strong problem-solving skills and attention to detail
- Excellent communication skills with ability to translate technical concepts for non-technical stakeholders
- Experience working in fast-paced, collaborative environments
- Self-motivated with ability to manage multiple priorities
Who We Are
Schonfeld is a global multi-manager hedge fund that strives to deliver industry-leading risk-adjusted returns for our investors. We leverage both internal and external portfolio manager teams around the world, seeking to capitalize on inefficiencies and opportunities within the markets. We draw from decades of experience and a significant investment in proprietary technology, infrastructure and risk analytics to invest across four main strategies: Quant, Tactical, Fundamental Equity and Discretionary Macro & Fixed Income.
Our Culture
At Schonfeld, we’ll invest in you. Attracting and retaining top talent is at the heart of what we do, because we believe that exceptional outcomes begin with exceptional people. We foster a culture where talent is empowered to continually learn, innovate and pursue ambitious goals. We are teamwork-oriented, collaborative and encourage ideas—at all levels—to be shared. As an organization committed to investing in our people, we provide learning and educational offerings and opportunities to make an impact. We encourage community through internal networks, external partnerships and service initiatives that promote inclusion and purpose beyond the firm’s walls.
The base pay for this role is expected to be between $225k and $275k. The expected base pay range is based on information at the time this post was generated. This role may also be eligible for other forms of compensation such as a performance bonus and a competitive benefits package. Actual compensation for the successful candidate will be determined based on a variety of factors such as skills, qualifications, and experience.
About The Role
Schonfeld Strategic Advisors is seeking an experienced AI Data Engineer to join our Data Engineering team. In this role, you will be responsible for designing, building, and maintaining robust data pipelines that power SchonAI, our firm's internal AI platform. You will work at the intersection of data engineering and AI, ensuring that high-quality, timely, and relevant data flows seamlessly to our AI systems to support investment professionals across the firm.
Key Responsibilities
Data Pipeline Development
- Design and build scalable, reliable data pipelines to ingest, transform, and deliver structured and unstructured data to SchonAI using Prefect.
- Develop ETL/ELT processes for diverse data sources including market data, research documents, internal databases, and third-party APIs.
- Implement real-time and batch data processing workflows to meet varying latency requirements.
- Ensure data quality, consistency, and integrity across all pipelines.
AI Data Infrastructure
- Build and maintain data infrastructure optimized for AI/ML workloads, including vector databases and semantic search systems.
- Design data schemas and storage solutions that support efficient retrieval and processing for LLM applications.
- Implement data versioning, lineage tracking, and observability for AI training and inference pipelines.
- Optimize data delivery for low-latency AI interactions and high-throughput batch processing.
Integration & Collaboration
- Partner with AI engineers, software developers, and data scientists to understand data requirements.
- Integrate with existing firm systems including risk platforms, trading systems, portfolio management tools, and research databases.
- Collaborate with infrastructure teams on cloud architecture, security, and compliance requirements.
- Work closely with business stakeholders to prioritize data sources and pipeline enhancements.
Data Governance & Security
- Implement appropriate data access controls, encryption, and compliance measures.
- Ensure adherence to data governance policies and regulatory requirements.
- Monitor and maintain data pipeline performance, reliability, and cost efficiency.
- Document data flows, transformations, and dependencies.
Required Qualifications
Technical Skills
- Programming: Strong proficiency in Python; experience with SQL and at least one other language (e.g. Java, Scala, Go, Rust)
- Data Engineering: 5+ years of experience building production data pipelines using tools like Apache Airflow, Prefect, Dagster, or similar
- Big Data Technologies: Hands-on experience with distributed computing frameworks (Spark, Flink) and modern data platforms
- Cloud Platforms: Proficiency with AWS services (S3, Kubernetes) or equivalent GCP services
- Databases: Experience with both SQL (PostgreSQL, MySQL) and NoSQL databases (MongoDB, DynamoDB, Elasticsearch)
- AI/ML Data: Understanding of data requirements for ML/AI systems, including experience with vector databases (Pinecone, Weaviate, Qdrant) and embedding pipelines
Preferred Experience
- Experience building data pipelines for LLM applications or RAG (Retrieval Augmented Generation) systems
- Familiarity with financial data sources (market data, fundamental data, alternative data)
- Knowledge of data streaming technologies (Kafka, Kinesis, Pub/Sub)
- Experience of Analytics/Warehouse/OLAP DB (BigQ, SingleStore, RedShift, ClickHouse)
- Experience with containerization (Docker) and orchestration (Kubernetes)
- Understanding of MLOps practices and tools
- Experience with data quality frameworks (Great Expectations, Deequ)
Professional Skills
- Bachelor's or Master's degree in Computer Science, Data Engineering, or related technical field
- Strong problem-solving skills and attention to detail
- Excellent communication skills with ability to translate technical concepts for non-technical stakeholders
- Experience working in fast-paced, collaborative environments
- Self-motivated with ability to manage multiple priorities
Who We Are
Schonfeld is a global multi-manager hedge fund that strives to deliver industry-leading risk-adjusted returns for our investors. We leverage both internal and external portfolio manager teams around the world, seeking to capitalize on inefficiencies and opportunities within the markets. We draw from decades of experience and a significant investment in proprietary technology, infrastructure and risk analytics to invest across four main strategies: Quant, Tactical, Fundamental Equity and Discretionary Macro & Fixed Income.
Our Culture
At Schonfeld, we’ll invest in you. Attracting and retaining top talent is at the heart of what we do, because we believe that exceptional outcomes begin with exceptional people. We foster a culture where talent is empowered to continually learn, innovate and pursue ambitious goals. We are teamwork-oriented, collaborative and encourage ideas—at all levels—to be shared. As an organization committed to investing in our people, we provide learning and educational offerings and opportunities to make an impact. We encourage community through internal networks, external partnerships and service initiatives that promote inclusion and purpose beyond the firm’s walls.
The base pay for this role is expected to be between $225k and $275k. The expected base pay range is based on information at the time this post was generated. This role may also be eligible for other forms of compensation such as a performance bonus and a competitive benefits package. Actual compensation for the successful candidate will be determined based on a variety of factors such as skills, qualifications, and experience.
AI Data Engineer Job Roles in New York
See all 549+ AI Data Engineer Jobs in New York
Sign up for free to filter by visa type, set job alerts, and find employers with verified sponsorship history.
Search AI Data Engineer Jobs in New YorkAI Data Engineer Jobs in New York: Frequently Asked Questions
Which companies sponsor visas for AI data engineers in New York?
Large financial institutions and tech firms are the most consistent sponsors in New York. JPMorgan Chase, Citigroup, IBM, Bloomberg, Google, Amazon, and Meta all have significant New York engineering operations and documented H-1B visa sponsorship histories. Mid-size fintech companies and AI startups in Manhattan and Brooklyn also sponsor, though less predictably than established enterprises with dedicated immigration HR teams.
Which visa types are most common for AI data engineer roles in New York?
The H-1B is the most common visa for AI data engineers in New York, as the role typically qualifies as a specialty occupation requiring a bachelor's degree or higher in computer science, data science, or a related field. OPT and STEM OPT are common entry points for graduates of New York universities. Candidates with extraordinary ability in AI research may qualify for the O-1A, which has no annual lottery.
Which cities in New York have the most AI data engineer sponsorship jobs?
Manhattan accounts for the large majority of AI data engineer sponsorship jobs in New York, driven by the concentration of finance, media, and enterprise tech employers. Brooklyn's tech scene, particularly in DUMBO and the Navy Yard area, has grown substantially. Albany sees some state government and university-affiliated roles, but the overwhelming concentration of sponsored positions remains in New York City.
How to find ai data engineer visa sponsorship jobs in New York?
Migrate Mate filters AI data engineer jobs specifically by visa sponsorship availability, so you can search New York roles without manually screening out employers who don't sponsor. The platform aggregates positions from companies with verified sponsorship histories, which is particularly useful given how varied sponsorship willingness is across New York's mix of large financial firms, enterprise tech employers, and early-stage AI startups.
Are there state-specific considerations for AI data engineers seeking sponsorship in New York?
New York's prevailing wage requirements under H-1B rules reflect the city's high cost of living, so employers sponsoring AI data engineers in Manhattan typically offer compensation benchmarked against DOL wage levels for the New York metropolitan area. Columbia, NYU, and Cornell Tech produce a strong pipeline of international candidates, meaning sponsored roles often attract highly competitive applicant pools. The density of AI investment in the city also means sponsoring employers expect demonstrated experience with production ML systems, not just academic exposure.
What is the prevailing wage for sponsored ai data engineer jobs in New York?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.