Data Engineer Visa Sponsorship Jobs in New York
New York's data engineering market spans finance, media, and tech, with major employers like JPMorgan Chase, Bloomberg, Spotify, and Palantir actively hiring in Manhattan and Brooklyn. The city's concentration of data-intensive industries makes it one of the most active states for data engineer visa sponsorship, particularly for H-1B petitions filed by large financial and technology firms.
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Your role at GEI.
The Data Engineer is responsible for designing, building, and maintaining the data pipelines and integrations that power GEI’s AI solutions and digital initiatives. This role focuses on ensuring enterprise data is accessible, reliable, and governed so that AI capabilities can be deployed and scaled with confidence.
The Data Engineer plays a hands-on role by preparing and integrating the data foundations that AI solutions depend on. This includes building ingestion pipelines, managing data stores, implementing quality and governance controls, and supporting retrieval patterns such as RAG. This role works closely with AI Engineers, solution architects, and platform teams to ensure data infrastructure is production-ready, secure, and aligned with GEI standards.
Essential Responsibilities & Duties
- Design, build, and maintain data pipelines that ingest, transform, and deliver enterprise data to AI solutions and business applications.
- Develop and manage integrations across enterprise data sources using APIs, Graph connectors, event-driven architectures, and batch/streaming patterns.
- Build and maintain data stores and indexing infrastructure that support retrieval-augmented generation (RAG) and other AI consumption patterns.
- Implement data quality, validation, and lineage controls to ensure accuracy and trustworthiness of data feeding AI workflows.
- Support and optimize data models underpinning Power BI dashboards and AI-enabled analytics.
- Collaborate with AI Engineers to define data contracts and ensure pipeline outputs meet solution requirements for schema, latency, and freshness.
- Instrument data pipelines for monitoring, alerting, cost control, and performance optimization.
- Implement data governance and security controls including access management, encryption, and compliance with organizational data policies.
- Identify data-related risks and support mitigation strategies in collaboration with architecture and platform teams.
Minimum Qualifications
- 4+ years of data engineering experience, with demonstrated ability to build and operate production data pipelines.
- Proficiency in Python and SQL; experience with PySpark or Spark is strongly preferred.
- Experience with Azure data services, including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, and Azure SQL.
- Familiarity with Azure AI Search, Cosmos DB, or similar services used to support AI retrieval and storage patterns.
- Experience building and managing ETL/ELT pipelines with structured, semi-structured, and unstructured data sources.
- Knowledge of data modeling, schema design, and indexing strategies for both analytical and AI workloads.
- Familiarity with infrastructure-as-code and CI/CD practices for data pipeline deployment (e.g., Terraform, Azure DevOps).
- Knowledge of data governance principles, including data cataloging, lineage, access control, and privacy requirements.
- Knowledge of security best practices for data solutions, including encryption at rest and in transit, role-based access control, and private networking.
- Experience with Databricks, including Delta Lake and Unity Catalog, is a plus.
- Prior experience in professional services, engineering, or construction environments is a plus.
- Azure or Databricks certifications (e.g., Azure Data Engineer Associate, Azure Solutions Architect Expert, Databricks Data Engineer Professional) are a plus.
We are GEI.
Some of the world’s most pressing problems – from climate change to sustainable development, to critical infrastructure and the future of our energy supply – need our brightest and diverse minds working together to create safer, more resilient communities for tomorrow.
We are technical experts, collaborators, and entrepreneurs who draw from diverse backgrounds to solve our clients’ most complex challenges.
With several offices across North America, we offer a range of engineering, science, and technical consulting services. Our range of expertise, project types, and culture make us the choice for top talent in the AEC industry.
Employee-owned. Employee-focused.
As an employee-owned company, our employees support our flat leadership structure, have a say in how our business operates and benefit from our financial success. We are committed to employee growth with career development opportunities, competitive total rewards, a well-being program, flexible work arrangements and more. Our company culture is driven by our 4 Cs – we are Client-Centered, Curious, Collaborative, and Community Minded – which support our focus on sustainability, safety, diversity, equity and inclusion.
GEI’s Total Rewards Package Includes
- Market-Competitive Compensation, including Eligibility for an Annual Performance Bonus
- Pay Range For This Position: $90,000.00 – $150,000.00/year
- Comprehensive Benefits Program, including Medical, Dental, Vision, Life, Disability and More
- Well-Being Program and Paid Parental Leave
- Commuter Benefits
- Hybrid Work Schedules and Cell Phone Stipends
- GEI University (GEIU) with Continuing Education Assistance and Tuition Reimbursement
- Connecting Conversation Program with a Focus on Professional Development and Opportunities for Advancement
- Support and Financial Rewards for Publication Awards, Professional Dues, and Professional Licenses
- Paid Holidays and Generous Paid Time Off Program
- Rewards and Recognition
- GEI-Funded Profit Sharing and 401(k)
- Opportunity to be an Owner and Shareholder
- A Vibrant Culture that is Focused on Partnership, Sustainability, Giving Back to Our Communities and Diversity, Equity and Inclusion
- And More…
Physical Requirements
WORK ENVIRONMENT
Functional Demands:
Sedentary
Light
Medium
Other
Activity Level Throughout Workday (check one per row)
Physical Activity Requirements
Occasional
(0-35% of day)
Frequent
(33-66% of day)
Continuous
(67-100% of day)
Not Applicable
Sitting
x
Standing
x
Walking
x
Climbing
x
Lifting (floor to waist level) (in pounds)
x
Lifting (waist level and above) (in pounds)
x
Carrying objects
x
Push/pull
x
Twisting
x
Bending
x
Reaching forward
x
Reaching overhead
x
Squat/kneel/crawl
x
Wrist position deviation
x
Pinching/fine motor skills
x
Keyboard use/repetitive motion
x
Taste or smell (taste=never)
x
Talk or hear
x
Accurate 20/40
Very Accurate 20/20
Not Applicable
Near Vision
x
Far Vision
x
Yes
No
Not Applicable
Color Discrimination Sensory Requirements
Minimal
Moderate
Accurate
Not Applicable
Depth perception
x
Hearing
x
Environment Requirements
Occupational Exposure Risk Potential
Reasonably Anticipated
Not Anticipated
Blood borne pathogens
x
Chemical
x
Airborne communicable diseases
x
Extreme temperatures
x
Radiation
x
Uneven surfaces or elevations
x
Extreme noise levels
x
Dust/particulate matter
x
Other (exposure risks):
Usual workday hours:
x
8
10
12
Other work hours
GEI is an AA/equal opportunity employer, including disabled and veterans.
Description
Your role at GEI.
The Data Engineer is responsible for designing, building, and maintaining the data pipelines and integrations that power GEI’s AI solutions and digital initiatives. This role focuses on ensuring enterprise data is accessible, reliable, and governed so that AI capabilities can be deployed and scaled with confidence.
The Data Engineer plays a hands-on role by preparing and integrating the data foundations that AI solutions depend on. This includes building ingestion pipelines, managing data stores, implementing quality and governance controls, and supporting retrieval patterns such as RAG. This role works closely with AI Engineers, solution architects, and platform teams to ensure data infrastructure is production-ready, secure, and aligned with GEI standards.
Essential Responsibilities & Duties
- Design, build, and maintain data pipelines that ingest, transform, and deliver enterprise data to AI solutions and business applications.
- Develop and manage integrations across enterprise data sources using APIs, Graph connectors, event-driven architectures, and batch/streaming patterns.
- Build and maintain data stores and indexing infrastructure that support retrieval-augmented generation (RAG) and other AI consumption patterns.
- Implement data quality, validation, and lineage controls to ensure accuracy and trustworthiness of data feeding AI workflows.
- Support and optimize data models underpinning Power BI dashboards and AI-enabled analytics.
- Collaborate with AI Engineers to define data contracts and ensure pipeline outputs meet solution requirements for schema, latency, and freshness.
- Instrument data pipelines for monitoring, alerting, cost control, and performance optimization.
- Implement data governance and security controls including access management, encryption, and compliance with organizational data policies.
- Identify data-related risks and support mitigation strategies in collaboration with architecture and platform teams.
Minimum Qualifications
- 4+ years of data engineering experience, with demonstrated ability to build and operate production data pipelines.
- Proficiency in Python and SQL; experience with PySpark or Spark is strongly preferred.
- Experience with Azure data services, including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, and Azure SQL.
- Familiarity with Azure AI Search, Cosmos DB, or similar services used to support AI retrieval and storage patterns.
- Experience building and managing ETL/ELT pipelines with structured, semi-structured, and unstructured data sources.
- Knowledge of data modeling, schema design, and indexing strategies for both analytical and AI workloads.
- Familiarity with infrastructure-as-code and CI/CD practices for data pipeline deployment (e.g., Terraform, Azure DevOps).
- Knowledge of data governance principles, including data cataloging, lineage, access control, and privacy requirements.
- Knowledge of security best practices for data solutions, including encryption at rest and in transit, role-based access control, and private networking.
- Experience with Databricks, including Delta Lake and Unity Catalog, is a plus.
- Prior experience in professional services, engineering, or construction environments is a plus.
- Azure or Databricks certifications (e.g., Azure Data Engineer Associate, Azure Solutions Architect Expert, Databricks Data Engineer Professional) are a plus.
We are GEI.
Some of the world’s most pressing problems – from climate change to sustainable development, to critical infrastructure and the future of our energy supply – need our brightest and diverse minds working together to create safer, more resilient communities for tomorrow.
We are technical experts, collaborators, and entrepreneurs who draw from diverse backgrounds to solve our clients’ most complex challenges.
With several offices across North America, we offer a range of engineering, science, and technical consulting services. Our range of expertise, project types, and culture make us the choice for top talent in the AEC industry.
Employee-owned. Employee-focused.
As an employee-owned company, our employees support our flat leadership structure, have a say in how our business operates and benefit from our financial success. We are committed to employee growth with career development opportunities, competitive total rewards, a well-being program, flexible work arrangements and more. Our company culture is driven by our 4 Cs – we are Client-Centered, Curious, Collaborative, and Community Minded – which support our focus on sustainability, safety, diversity, equity and inclusion.
GEI’s Total Rewards Package Includes
- Market-Competitive Compensation, including Eligibility for an Annual Performance Bonus
- Pay Range For This Position: $90,000.00 – $150,000.00/year
- Comprehensive Benefits Program, including Medical, Dental, Vision, Life, Disability and More
- Well-Being Program and Paid Parental Leave
- Commuter Benefits
- Hybrid Work Schedules and Cell Phone Stipends
- GEI University (GEIU) with Continuing Education Assistance and Tuition Reimbursement
- Connecting Conversation Program with a Focus on Professional Development and Opportunities for Advancement
- Support and Financial Rewards for Publication Awards, Professional Dues, and Professional Licenses
- Paid Holidays and Generous Paid Time Off Program
- Rewards and Recognition
- GEI-Funded Profit Sharing and 401(k)
- Opportunity to be an Owner and Shareholder
- A Vibrant Culture that is Focused on Partnership, Sustainability, Giving Back to Our Communities and Diversity, Equity and Inclusion
- And More…
Physical Requirements
WORK ENVIRONMENT
Functional Demands:
Sedentary
Light
Medium
Other
Activity Level Throughout Workday (check one per row)
Physical Activity Requirements
Occasional
(0-35% of day)
Frequent
(33-66% of day)
Continuous
(67-100% of day)
Not Applicable
Sitting
x
Standing
x
Walking
x
Climbing
x
Lifting (floor to waist level) (in pounds)
x
Lifting (waist level and above) (in pounds)
x
Carrying objects
x
Push/pull
x
Twisting
x
Bending
x
Reaching forward
x
Reaching overhead
x
Squat/kneel/crawl
x
Wrist position deviation
x
Pinching/fine motor skills
x
Keyboard use/repetitive motion
x
Taste or smell (taste=never)
x
Talk or hear
x
Accurate 20/40
Very Accurate 20/20
Not Applicable
Near Vision
x
Far Vision
x
Yes
No
Not Applicable
Color Discrimination Sensory Requirements
Minimal
Moderate
Accurate
Not Applicable
Depth perception
x
Hearing
x
Environment Requirements
Occupational Exposure Risk Potential
Reasonably Anticipated
Not Anticipated
Blood borne pathogens
x
Chemical
x
Airborne communicable diseases
x
Extreme temperatures
x
Radiation
x
Uneven surfaces or elevations
x
Extreme noise levels
x
Dust/particulate matter
x
Other (exposure risks):
Usual workday hours:
x
8
10
12
Other work hours
GEI is an AA/equal opportunity employer, including disabled and veterans.
Data Engineer Job Roles in New York
See all 1,775+ Data Engineer Jobs in New York
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Search Data Engineer Jobs in New YorkData Engineer Jobs in New York: Frequently Asked Questions
Which companies sponsor visas for data engineers in New York?
Financial institutions and technology companies are the most consistent sponsors. JPMorgan Chase, Goldman Sachs, Bloomberg, Spotify, Palantir, and Verizon have all filed H-1B petitions for data engineer roles in New York. Large consulting firms including Deloitte and Accenture also sponsor data engineers placed at New York client sites. Sponsorship activity is heaviest among employers with established global hiring programs and dedicated immigration teams.
Which visa types are most common for data engineer roles in New York?
The H-1B is the most common visa for data engineers in New York, as the role typically qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, information systems, or a related field. Candidates already in the U.S. on F-1 OPT or STEM OPT frequently receive H-1B sponsorship from New York employers. The O-1A is another pathway for engineers with a strong record of publications, patents, or industry recognition.
Which cities in New York have the most data engineer sponsorship jobs?
Manhattan accounts for the large majority of data engineer sponsorship jobs in New York, driven by the financial services sector concentrated in Midtown and Lower Manhattan. Brooklyn's tech corridor, particularly around DUMBO and the Navy Yard, has grown as a secondary hub with startups and mid-size technology companies. Buffalo and Albany have a smaller but growing presence, largely tied to state government technology initiatives and regional university research partnerships.
How to find data engineer visa sponsorship jobs in New York?
Migrate Mate filters job listings specifically for roles where employers have a documented history of visa sponsorship, which saves significant time when targeting data engineer positions in New York. You can browse by role and state to surface openings at financial institutions, tech companies, and consulting firms that have filed H-1B petitions in New York. This is especially useful for F-1 OPT holders and candidates actively managing tight sponsorship timelines.
Are there any New York-specific considerations for data engineer visa sponsorship?
New York employers must meet Department of Labor prevailing wage requirements specific to the New York metropolitan area, which are determined by the location where work is actually performed. Data engineers in hybrid or remote arrangements need to confirm with their employer which worksite location is listed on the Labor Condition Application, as this affects the applicable prevailing wage. New York's large university system, including NYU and Columbia, produces a significant share of candidates entering the H-1B pipeline each cycle.
What is the prevailing wage for sponsored 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.
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