Senior Staff Data Engineer Jobs in USA with Visa Sponsorship
Senior Staff Data Engineer roles attract H-1B visa, O-1 visa, and L-1 visa sponsorship from tech, finance, and healthcare employers. At this seniority level, employers routinely sponsor because replacing this expertise is harder than filing the petition. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsINTRODUCTION
GE Vernova's Gas Power Data Science organization is building an enterprise ontology and knowledge graph capability to give AI agents, GenAI applications, and advanced analytics a shared, governed representation of the business. We're looking for a Senior Ontology & Knowledge Graph modeling to own the ontology and knowledge graph strategy across all of Gas Power including services, engineering, and commercial domains, ensuring they interoperate as one coherent semantic layer rather than a set of individually correct but disconnected models. You'll build the semantic "connective tissue" that lets Gas Power derive intelligence from its industrial data, leading the shift from traditional data management to an AI-ready semantic ecosystem that enables advanced diagnostics, predictive maintenance, and strategic decision-making.
This is a program level role. You remain technically hands on enough to build and debug models when it matters, but your time is weighted toward setting modeling standards, resolving cross-domain conflicts, and acting as the final technical authority on ontology. You own how the organization scales its model-building capability training approach, and delivery process for contractors, FDEs (Forward Deployed Engineers), and SMEs across the entire program, and you are accountable for the organization's overall ontology capability, not just the output of any single domain.
You will define and own the semantic model governance framework end to end, versioning policy, lifecycle, access model, and how governance holds up as adoption scales, and you will own the platform selection decision and long-term roadmap.
ROLE AND RESPONSIBILITIES
- Own the ontology and knowledge graph strategy across all Gas Power domains: services, engineering, and commercial, ensuring domain models interoperate as one coherent semantic layer.
- Set enterprise-wide modeling standards and patterns (OWL 2, RDF/RDFS, SHACL, SPARQL) that all domain models must follow.
- Resolve cross-domain modeling conflicts and serve as the final technical authority when domain models compete or overlap.
- Design and own the organization's model for scaling ontology work: how contractors, FDEs, and SMEs are staffed, trained, and deployed across the full program.
- Build and evolve the training curriculum that brings SMEs to self-sufficiency in building and maintaining their own domain models.
- Own the organization's overall ontology building capability, measured not by any single domain's output, but by how well the program scales without bottlenecking on any one person.
- Define the model approval framework: review criteria, review board/process, and escalation path for contested or high-risk models.
- Serve as final arbiter on contested or high-risk model approvals, while delegating day-to-day approvals within the defined framework.
- Own the semantic model governance framework end to end: versioning policy, model lifecycle, access model, and metadata/lineage management.
- Ensure governance scales as the knowledge graph grows, auditing for drift, inconsistency, and standards erosion across domains.
- Partner with the GenAI/ML and AI platform teams to ensure the knowledge graph is the grounding layer for RAG and agentic workflows program-wide.
- Communicate modeling trade-offs, and delivery progress clearly to technical teams and senior stakeholders.
- Contribute reusable standards, reference documentation, and mentoring that strengthen ontology and semantic modeling capability across the team.
BASIC QUALIFICATIONS
- Bachelor’s degree in computer science, information science, data science, engineering, or a related field, or equivalent practical experience.
- 4-6 years of professional experience in data modeling, semantic technologies, or knowledge engineering, including at least 1-2 years working directly with ontologies.
- Professional experience delivering data models, semantic technologies, or knowledge engineering solutions, including direct work with ontologies or knowledge graphs.
- Hands-on proficiency with OWL 2, RDF/RDFS, SHACL, and SPARQL.
- Experience with at least one ontology, graph, or semantic modeling platform or tool, such as Neo4j, Protégé, Palantir Foundry, or Atlan.
- Working knowledge of modern cloud data environments and the integration patterns required to connect semantic layers to enterprise data products.
- Demonstrated ability to independently deliver a defined technical scope within a broader architecture and product roadmap.
- Strong communication and stakeholder-management skills, with the ability to convert ambiguous requirements into clear semantic models and recommendations.
- Demonstrated ability to work independently on a defined scope while collaborating within a broader technical roadmap.
PREFERRED QUALIFICATIONS
- Experience in an industrial, energy, or manufacturing environment (services demand, asset performance, or engineering data domains a plus).
- Exposure to GenAI/LLM applications, particularly RAG architectures grounded in structured knowledge.
- Familiarity with MCP (Model Context Protocol) or similar agent-to-data integration patterns.
- Experience contributing to platform evaluation or architecture decision documents for executive audiences.
- Knowledge of data governance, metadata management, or MLOps practices (MLflow or similar).
ADDITIONAL INFORMATION
GE Vernova offers a great work environment, professional development, challenging careers, and competitive compensation. GE Vernova is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE Vernova will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
Relocation Assistance Provided: No
For candidates applying to a U.S. based position, the pay range for this position is between $119,200.00 and $198,600.00. The Company pays a geographic differential of 110%, 120% or 130% of salary in certain areas. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set.
Bonus eligibility: discretionary annual bonus.
This posting is expected to remain open for at least seven days after it was posted on October 08, 2026.
Available benefits include medical, dental, vision, and prescription drug coverage; access to Health Coach from GE Vernova, a 24/7 nurse-based resource; and access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services. Retirement benefits include the GE Vernova Retirement Savings Plan, a tax-advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions, as well as access to Fidelity resources and financial planning consultants. Other benefits include tuition assistance, adoption assistance, paid parental leave, disability benefits, life insurance, 12 paid holidays, and permissive time off.
GE Vernova Inc. or its affiliates (collectively or individually, “GE Vernova”) sponsor certain employee benefit plans or programs GE Vernova reserves the right to terminate, amend, suspend, replace, or modify its benefit plans and programs at any time and for any reason, in its sole discretion. No individual has a vested right to any benefit under a GE Vernova welfare benefit plan or program. This document does not create a contract of employment with any individual.
INTRODUCTION
GE Vernova's Gas Power Data Science organization is building an enterprise ontology and knowledge graph capability to give AI agents, GenAI applications, and advanced analytics a shared, governed representation of the business. We're looking for a Senior Ontology & Knowledge Graph modeling to own the ontology and knowledge graph strategy across all of Gas Power including services, engineering, and commercial domains, ensuring they interoperate as one coherent semantic layer rather than a set of individually correct but disconnected models. You'll build the semantic "connective tissue" that lets Gas Power derive intelligence from its industrial data, leading the shift from traditional data management to an AI-ready semantic ecosystem that enables advanced diagnostics, predictive maintenance, and strategic decision-making.
This is a program level role. You remain technically hands on enough to build and debug models when it matters, but your time is weighted toward setting modeling standards, resolving cross-domain conflicts, and acting as the final technical authority on ontology. You own how the organization scales its model-building capability training approach, and delivery process for contractors, FDEs (Forward Deployed Engineers), and SMEs across the entire program, and you are accountable for the organization's overall ontology capability, not just the output of any single domain.
You will define and own the semantic model governance framework end to end, versioning policy, lifecycle, access model, and how governance holds up as adoption scales, and you will own the platform selection decision and long-term roadmap.
ROLE AND RESPONSIBILITIES
- Own the ontology and knowledge graph strategy across all Gas Power domains: services, engineering, and commercial, ensuring domain models interoperate as one coherent semantic layer.
- Set enterprise-wide modeling standards and patterns (OWL 2, RDF/RDFS, SHACL, SPARQL) that all domain models must follow.
- Resolve cross-domain modeling conflicts and serve as the final technical authority when domain models compete or overlap.
- Design and own the organization's model for scaling ontology work: how contractors, FDEs, and SMEs are staffed, trained, and deployed across the full program.
- Build and evolve the training curriculum that brings SMEs to self-sufficiency in building and maintaining their own domain models.
- Own the organization's overall ontology building capability, measured not by any single domain's output, but by how well the program scales without bottlenecking on any one person.
- Define the model approval framework: review criteria, review board/process, and escalation path for contested or high-risk models.
- Serve as final arbiter on contested or high-risk model approvals, while delegating day-to-day approvals within the defined framework.
- Own the semantic model governance framework end to end: versioning policy, model lifecycle, access model, and metadata/lineage management.
- Ensure governance scales as the knowledge graph grows, auditing for drift, inconsistency, and standards erosion across domains.
- Partner with the GenAI/ML and AI platform teams to ensure the knowledge graph is the grounding layer for RAG and agentic workflows program-wide.
- Communicate modeling trade-offs, and delivery progress clearly to technical teams and senior stakeholders.
- Contribute reusable standards, reference documentation, and mentoring that strengthen ontology and semantic modeling capability across the team.
BASIC QUALIFICATIONS
- Bachelor’s degree in computer science, information science, data science, engineering, or a related field, or equivalent practical experience.
- 4-6 years of professional experience in data modeling, semantic technologies, or knowledge engineering, including at least 1-2 years working directly with ontologies.
- Professional experience delivering data models, semantic technologies, or knowledge engineering solutions, including direct work with ontologies or knowledge graphs.
- Hands-on proficiency with OWL 2, RDF/RDFS, SHACL, and SPARQL.
- Experience with at least one ontology, graph, or semantic modeling platform or tool, such as Neo4j, Protégé, Palantir Foundry, or Atlan.
- Working knowledge of modern cloud data environments and the integration patterns required to connect semantic layers to enterprise data products.
- Demonstrated ability to independently deliver a defined technical scope within a broader architecture and product roadmap.
- Strong communication and stakeholder-management skills, with the ability to convert ambiguous requirements into clear semantic models and recommendations.
- Demonstrated ability to work independently on a defined scope while collaborating within a broader technical roadmap.
PREFERRED QUALIFICATIONS
- Experience in an industrial, energy, or manufacturing environment (services demand, asset performance, or engineering data domains a plus).
- Exposure to GenAI/LLM applications, particularly RAG architectures grounded in structured knowledge.
- Familiarity with MCP (Model Context Protocol) or similar agent-to-data integration patterns.
- Experience contributing to platform evaluation or architecture decision documents for executive audiences.
- Knowledge of data governance, metadata management, or MLOps practices (MLflow or similar).
ADDITIONAL INFORMATION
GE Vernova offers a great work environment, professional development, challenging careers, and competitive compensation. GE Vernova is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE Vernova will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
Relocation Assistance Provided: No
For candidates applying to a U.S. based position, the pay range for this position is between $119,200.00 and $198,600.00. The Company pays a geographic differential of 110%, 120% or 130% of salary in certain areas. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set.
Bonus eligibility: discretionary annual bonus.
This posting is expected to remain open for at least seven days after it was posted on October 08, 2026.
Available benefits include medical, dental, vision, and prescription drug coverage; access to Health Coach from GE Vernova, a 24/7 nurse-based resource; and access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services. Retirement benefits include the GE Vernova Retirement Savings Plan, a tax-advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions, as well as access to Fidelity resources and financial planning consultants. Other benefits include tuition assistance, adoption assistance, paid parental leave, disability benefits, life insurance, 12 paid holidays, and permissive time off.
GE Vernova Inc. or its affiliates (collectively or individually, “GE Vernova”) sponsor certain employee benefit plans or programs GE Vernova reserves the right to terminate, amend, suspend, replace, or modify its benefit plans and programs at any time and for any reason, in its sole discretion. No individual has a vested right to any benefit under a GE Vernova welfare benefit plan or program. This document does not create a contract of employment with any individual.
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Get Access To All JobsTips for Finding Visa Sponsorship as a Senior Staff Data Engineer
Target employers with established H-1B track records
Companies that have filed H-1B petitions for data engineering roles in prior years are far more likely to sponsor again. Consistent filing history signals an internal process, legal counsel on retainer, and leadership buy-in for international hires.
Position your seniority as the sponsorship justification
Staff and Senior Staff titles signal specialized expertise that's genuinely hard to source domestically. Frame your experience around proprietary systems, large-scale architecture, and cross-functional leadership, which strengthens the specialty occupation argument in the H-1B petition.
Raise the visa conversation after demonstrating value
Bring up sponsorship after a technical screen or take-home, not in the first outreach. At this level, hiring managers have budget flexibility, but they need confidence in the hire before committing to the legal and administrative overhead of a petition.
Ask specifically about cap-exempt employers
Universities, research institutions, and affiliated nonprofits are exempt from the H-1B lottery cap. Senior Staff Data Engineers at these organizations can receive H-1B approval year-round without competing in the annual lottery, which is a meaningful advantage.
Get your I-140 approved early if you're on an H-1B
Filing an EB-1B or EB-2 NIW I-140 petition early preserves your priority date and unlocks H-1B extensions beyond the standard six-year limit. At Senior Staff level, an approved I-140 also gives you more leverage in job negotiations.
Clarify whether the LCA covers your actual work location
If you're working remotely from a state different from the employer's listed address, the Labor Condition Application must reflect your physical work location. Mismatches can create compliance issues at renewal or during an RFE, so confirm this before accepting an offer.
Frequently Asked Questions
Which visa types do Senior Staff Data Engineers typically get sponsored for?
H-1B visa is the most common path. Data engineering at the Senior Staff level qualifies as a specialty occupation because the role requires at minimum a bachelor's degree in computer science, information systems, or a closely related field. O-1A is viable for engineers with documented impact, patents, published work, or industry recognition. L-1A or L-1B apply if you're transferring from an overseas office of the same employer.
Does a Senior Staff Data Engineer role qualify as a specialty occupation for H-1B purposes?
Yes, consistently. USCIS has approved H-1B petitions for data engineering roles across thousands of employers. The key requirement is that the position genuinely requires a specific bachelor's degree or higher, not just any degree. Senior Staff roles typically involve distributed systems, data architecture, or pipeline design at scale, which supports the specialty occupation argument clearly. USCIS RFEs on these petitions are relatively uncommon compared to more ambiguous titles.
Does my degree field matter for H-1B sponsorship as a data engineer?
Yes. The degree needs to relate directly to the role. Computer science, software engineering, data science, mathematics, and statistics all support a strong petition. If your degree is in an unrelated field, your employer's attorney will need to build the case around equivalent experience, which requires three years of relevant work experience for every year of missing education. A mismatch doesn't automatically disqualify you, but it adds complexity to the petition.
How competitive is H-1B sponsorship for Senior Staff Data Engineers compared to mid-level roles?
More favorable. Employers are more willing to absorb the cost and administrative effort for Senior Staff hires because the role is harder to backfill. The lottery odds are the same regardless of seniority, but at this level employers are more likely to use premium processing, engage experienced counsel, and respond quickly to RFEs. Cap-exempt employers remain an option worth prioritizing. You can browse Senior Staff Data Engineer roles with confirmed sponsorship on Migrate Mate.
Can I switch employers mid-H-1B as a Senior Staff Data Engineer?
Yes. Under H-1B portability, you can start working for a new employer as soon as they file an H-1B transfer petition, without waiting for approval, as long as your previous H-1B was valid and you're maintaining lawful status. The new employer files a new I-129 petition with an LCA covering your role and location. At Senior Staff level, this process is routine for employers who regularly hire visa holders.
What is the prevailing wage requirement for sponsored Senior Staff Data Engineer jobs?
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.