Senior Data Science Engineer Visa Sponsorship Jobs in North Carolina
North Carolina's senior data science engineer market is anchored by Research Triangle Park, one of the densest concentrations of tech and life sciences employers in the Southeast. Companies like SAS Institute, Red Hat, Lenovo, and Bank of America's Charlotte operations regularly hire for senior data science engineering roles and have established visa sponsorship programs for international candidates.
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Get Access To All JobsWork Schedule
Standard (Mon-Fri)
Environmental Conditions
Office
Job Description
When you join Thermo Fisher Scientific, you become part of a team that is committed to enabling discovery, improving outcomes, and driving meaningful impact through data. Within our Finance Digital Team, we are redefining how data is structured, accessed, and used to power decision-making across a complex, global organization.
This role sits at the intersection of data engineering, analytics, and finance. It is focused on building scalable data models, enabling advanced analytics, and shaping how data is used—not just building pipelines. You will work closely with data scientists, analysts, and finance leaders to design flexible, analytics-ready data structures, support data science initiatives and elevate the capabilities of the broader team.
Key Responsibilities:
- Own the design of analytical and semantic data models that support financial reporting, advanced analytics, and future capabilities
- Lead the development of scalable, analytics-ready data products
- Lead efforts and partner with data scientists and analysts to enable experimentation, feature engineering, and advanced analytics by shaping how data is modeled and accessed
- Translate complex business problems into flexible data solutions, working closely with Finance leadership to define requirements and deliver actionable insights
- Remain hands-on in Python, SQL, and Databricks/Spark environments, prototyping solutions and guiding technical implementation
- Lead and develop a cross-functional team of data engineers, analysts, and data scientists, building capabilities in modern data frameworks and analytical thinking
- Evaluate and introduce new technologies and approaches across Databricks, Microsoft Fabric, AI/ML, and data orchestration tools to continuously improve team effectiveness
Requirements/Qualifications:
- 8+ years of experience in data engineering, analytics engineering, data science, or related roles with increasing technical scope and ownership
- 2–5+ years of experience leading technical teams, with a track record of developing talent across data engineering, analytics, and/or data science
- Strong hands-on expertise in Python and SQL, with the ability to prototype, debug, and guide implementation directly
- Deep experience working in modern data platforms such as Databricks (preferred), Microsoft Fabric, or similar Spark/lakehouse environments
- Proven experience designing and implementing scalable data models and analytics-ready datasets (not just data pipelines), including support for BI and advanced analytics use cases
- Experience working closely with data scientists and analysts, enabling workflows such as experimentation, feature engineering, and advanced analytics
- Strong understanding of data modeling concepts (dimensional modeling, semantic layers, data products) and how they support business decision-making
- Experience translating ambiguous business problems into flexible, scalable data solutions
- Ability to operate effectively in evolving architectures and toolsets, balancing speed, flexibility, and governance (e.g., Databricks, Fabric, Unity Catalog)
- Familiarity with BI and visualization tools such as Power BI or Tableau
Preferred Qualifications
- Experience with semantic modeling or governed data layers (e.g., Unity Catalog, dbt, or similar)
- Background supporting finance, ERP, or operational data domains
- Exposure to AI/ML workflows and supporting infrastructure
- Experience with modern data practices such as version-controlled transformations, testing, and modular data design
- Familiarity with Agile or product-oriented delivery models
Work Schedule
Standard (Mon-Fri)
Environmental Conditions
Office
Job Description
When you join Thermo Fisher Scientific, you become part of a team that is committed to enabling discovery, improving outcomes, and driving meaningful impact through data. Within our Finance Digital Team, we are redefining how data is structured, accessed, and used to power decision-making across a complex, global organization.
This role sits at the intersection of data engineering, analytics, and finance. It is focused on building scalable data models, enabling advanced analytics, and shaping how data is used—not just building pipelines. You will work closely with data scientists, analysts, and finance leaders to design flexible, analytics-ready data structures, support data science initiatives and elevate the capabilities of the broader team.
Key Responsibilities:
- Own the design of analytical and semantic data models that support financial reporting, advanced analytics, and future capabilities
- Lead the development of scalable, analytics-ready data products
- Lead efforts and partner with data scientists and analysts to enable experimentation, feature engineering, and advanced analytics by shaping how data is modeled and accessed
- Translate complex business problems into flexible data solutions, working closely with Finance leadership to define requirements and deliver actionable insights
- Remain hands-on in Python, SQL, and Databricks/Spark environments, prototyping solutions and guiding technical implementation
- Lead and develop a cross-functional team of data engineers, analysts, and data scientists, building capabilities in modern data frameworks and analytical thinking
- Evaluate and introduce new technologies and approaches across Databricks, Microsoft Fabric, AI/ML, and data orchestration tools to continuously improve team effectiveness
Requirements/Qualifications:
- 8+ years of experience in data engineering, analytics engineering, data science, or related roles with increasing technical scope and ownership
- 2–5+ years of experience leading technical teams, with a track record of developing talent across data engineering, analytics, and/or data science
- Strong hands-on expertise in Python and SQL, with the ability to prototype, debug, and guide implementation directly
- Deep experience working in modern data platforms such as Databricks (preferred), Microsoft Fabric, or similar Spark/lakehouse environments
- Proven experience designing and implementing scalable data models and analytics-ready datasets (not just data pipelines), including support for BI and advanced analytics use cases
- Experience working closely with data scientists and analysts, enabling workflows such as experimentation, feature engineering, and advanced analytics
- Strong understanding of data modeling concepts (dimensional modeling, semantic layers, data products) and how they support business decision-making
- Experience translating ambiguous business problems into flexible, scalable data solutions
- Ability to operate effectively in evolving architectures and toolsets, balancing speed, flexibility, and governance (e.g., Databricks, Fabric, Unity Catalog)
- Familiarity with BI and visualization tools such as Power BI or Tableau
Preferred Qualifications
- Experience with semantic modeling or governed data layers (e.g., Unity Catalog, dbt, or similar)
- Background supporting finance, ERP, or operational data domains
- Exposure to AI/ML workflows and supporting infrastructure
- Experience with modern data practices such as version-controlled transformations, testing, and modular data design
- Familiarity with Agile or product-oriented delivery models
Senior Data Science Engineer Job Roles in North Carolina
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Search Senior Data Science Engineer Jobs in North CarolinaSenior Data Science Engineer Jobs in North Carolina: Frequently Asked Questions
Which companies sponsor visas for senior data science engineers in North Carolina?
SAS Institute in Cary is one of the most active sponsors for data science engineering talent in North Carolina, given its analytics-focused product line. Red Hat, Lenovo's North American headquarters in Morrisville, Fidelity Investments, and Bank of America in Charlotte also have documented H-1B sponsorship histories for senior data science engineering roles. Life sciences firms like Biogen and IQVIA, both with Triangle-area operations, hire senior data science engineers for clinical and research analytics work.
Which visa types are most common for senior data science engineer roles in North Carolina?
The H-1B is the most common visa for senior data science engineers in North Carolina, as the role typically qualifies as a specialty occupation requiring a bachelor's degree or higher in computer science, statistics, or a related field. Candidates with a master's degree may benefit from the advanced degree exemption during the H-1B lottery. Those with extraordinary research contributions may also explore the O-1A category. Canadians and Mexicans may qualify for TN status under the mathematician or computer systems analyst category, depending on role classification.
Which cities in North Carolina have the most senior data science engineer sponsorship jobs?
The Research Triangle area, covering Raleigh, Durham, Cary, and Chapel Hill, accounts for the largest share of senior data science engineer sponsorship activity in North Carolina. This concentration reflects the presence of major tech employers, university research partnerships with NC State, Duke, and UNC, and a dense biotech and pharma sector. Charlotte is the second-largest hub, driven by financial services firms that build data science teams for risk modeling, fraud detection, and customer analytics.
How to find senior data science engineer visa sponsorship jobs in North Carolina?
Migrate Mate filters senior data science engineer jobs in North Carolina specifically by visa sponsorship eligibility, so you're not sorting through postings from employers who don't sponsor. The platform is particularly useful for identifying roles at Research Triangle Park companies and Charlotte-based financial services firms, which represent the two main hiring centers for this role in the state. Search by job title and state to see current openings with sponsorship confirmed.
Are there any North Carolina-specific considerations for senior data science engineers seeking visa sponsorship?
North Carolina's concentration of research universities, including NC State, Duke, and UNC Chapel Hill, creates a strong local pipeline of data science talent, which means employer expectations for senior-level candidates are high. Roles tied to life sciences or pharmaceutical research in the Triangle may involve additional compliance considerations around data handling. Employers filing H-1B petitions must meet prevailing wage requirements set by the Department of Labor for the specific metro area, and Raleigh-Durham and Charlotte are classified separately, so wage levels differ between those markets.
What is the prevailing wage for sponsored senior data science engineer jobs in North Carolina?
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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