Senior Data Science Engineer Visa Sponsorship Jobs in Virginia
Virginia is a strong market for senior data science engineers seeking visa sponsorship, anchored by the technology corridor spanning Northern Virginia, Arlington, and Reston. Major employers include Booz Allen Hamilton, Leidos, Capital One, Amazon Web Services, and Accenture Federal Services, many of which have established H-1B sponsorship track records across data science and machine learning roles.
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Systems Planning and Analysis, Inc. (SPA) delivers high-impact, technical solutions to complex national security issues. With over 50 years of business expertise and consistent growth, we are known for continuous innovation for our government customers, in both the US and abroad. Our exceptionally talented team is highly collaborative in spirit and practice, producing Results that Matter. Come work with the best! We offer opportunity, unique challenges, and clear-sighted commitment to the mission. SPA: Objective. Responsive. Trusted.
As a Senior Data Engineer, you will design, build, and operate enterprise data pipelines and data models that transform operational data into secure, trusted, and accessible data products. This position works closely with Finance, Accounting, HR, Business Development, and SPA’s client-facing business units - requiring strong communication skills to translate technical concepts into clear, actionable information for diverse stakeholders.
Responsibilities:
Data Engineering & Architecture:
- Design, develop, and maintain scalable data pipelines and workflows across enterprise systems.
- Build well-structured data models, semantic layers, and curated datasets aligned with business needs.
- Implement data quality, observability, and reliability controls to ensure accuracy and auditability.
Integration, MDM & Platform Operations:
- Engineer integrations that synchronize master data across SPA systems.
- Partner with enterprise platform teams to leverage SPA-approved middleware, MDM, and Azure services.
- Implement CI/CD, IaC, and automation to manage data environments and deployments.
Communication & Cross-Functional Collaboration:
- Translate complex data engineering topics into clear, plain-language explanations for business, technical, and executive audiences.
- Work directly with stakeholders to understand data needs, document requirements, and communicate technical impacts.
- Act as a trusted partner to business units, collaborating on reporting, analytics, and process-improvement initiatives.
- Provide clear written documentation, diagrams, and briefings that support data governance, solution design, and adoption.
Security, Governance & Compliance:
- Implement secure data access patterns, encryption, retention, and lineage in alignment with SPA cybersecurity and compliance requirements.
- Support enterprise data governance practices and contribute to standardized data policies and definitions.
BI & Analytics Enablement:
- Partner with analysts to deliver high-quality, consumption-ready datasets for reporting tools.
- Provide guidance on data modeling, semantic layers, and best practices for BI enablement.
Continuous Improvement:
- Contribute to engineering standards, patterns, and documentation.
- Mentor junior engineers and analysts in engineering practices and communication techniques.
QUALIFICATIONS
Required:
- Bachelor’s degree in computer science, Information Systems, Data Science, or related field.
- 7+ years of experience building production-grade data pipelines and data models on modern cloud platforms.
- Experience supporting BI environments and semantic modeling (e.g., Power BI).
- Experience with data warehousing, Lakehouse architectures, ETL/ELT patterns, and data quality frameworks.
- Demonstrated ability to explain technical concepts clearly and concisely to non-technical audiences.
- Experience with MDM tools, middleware integrations, or enterprise master data synchronization.
- Experience with Azure data services, orchestration tools, and enterprise analytics platforms.
- Excellent communication skills - written, verbal, and visual - with the ability to tailor messaging to executives, business users, and engineering peers.
- Proven record of effective collaboration with cross-functional stakeholders.
Preferred:
- Background in government-contracting or regulated environments.
- Good SQL skills and proficiency in a programming language such as Python or Scala.
- Exposure to process engineering and change-management practices.
Overview:
Systems Planning and Analysis, Inc. (SPA) delivers high-impact, technical solutions to complex national security issues. With over 50 years of business expertise and consistent growth, we are known for continuous innovation for our government customers, in both the US and abroad. Our exceptionally talented team is highly collaborative in spirit and practice, producing Results that Matter. Come work with the best! We offer opportunity, unique challenges, and clear-sighted commitment to the mission. SPA: Objective. Responsive. Trusted.
As a Senior Data Engineer, you will design, build, and operate enterprise data pipelines and data models that transform operational data into secure, trusted, and accessible data products. This position works closely with Finance, Accounting, HR, Business Development, and SPA’s client-facing business units - requiring strong communication skills to translate technical concepts into clear, actionable information for diverse stakeholders.
Responsibilities:
Data Engineering & Architecture:
- Design, develop, and maintain scalable data pipelines and workflows across enterprise systems.
- Build well-structured data models, semantic layers, and curated datasets aligned with business needs.
- Implement data quality, observability, and reliability controls to ensure accuracy and auditability.
Integration, MDM & Platform Operations:
- Engineer integrations that synchronize master data across SPA systems.
- Partner with enterprise platform teams to leverage SPA-approved middleware, MDM, and Azure services.
- Implement CI/CD, IaC, and automation to manage data environments and deployments.
Communication & Cross-Functional Collaboration:
- Translate complex data engineering topics into clear, plain-language explanations for business, technical, and executive audiences.
- Work directly with stakeholders to understand data needs, document requirements, and communicate technical impacts.
- Act as a trusted partner to business units, collaborating on reporting, analytics, and process-improvement initiatives.
- Provide clear written documentation, diagrams, and briefings that support data governance, solution design, and adoption.
Security, Governance & Compliance:
- Implement secure data access patterns, encryption, retention, and lineage in alignment with SPA cybersecurity and compliance requirements.
- Support enterprise data governance practices and contribute to standardized data policies and definitions.
BI & Analytics Enablement:
- Partner with analysts to deliver high-quality, consumption-ready datasets for reporting tools.
- Provide guidance on data modeling, semantic layers, and best practices for BI enablement.
Continuous Improvement:
- Contribute to engineering standards, patterns, and documentation.
- Mentor junior engineers and analysts in engineering practices and communication techniques.
QUALIFICATIONS
Required:
- Bachelor’s degree in computer science, Information Systems, Data Science, or related field.
- 7+ years of experience building production-grade data pipelines and data models on modern cloud platforms.
- Experience supporting BI environments and semantic modeling (e.g., Power BI).
- Experience with data warehousing, Lakehouse architectures, ETL/ELT patterns, and data quality frameworks.
- Demonstrated ability to explain technical concepts clearly and concisely to non-technical audiences.
- Experience with MDM tools, middleware integrations, or enterprise master data synchronization.
- Experience with Azure data services, orchestration tools, and enterprise analytics platforms.
- Excellent communication skills - written, verbal, and visual - with the ability to tailor messaging to executives, business users, and engineering peers.
- Proven record of effective collaboration with cross-functional stakeholders.
Preferred:
- Background in government-contracting or regulated environments.
- Good SQL skills and proficiency in a programming language such as Python or Scala.
- Exposure to process engineering and change-management practices.
Senior Data Science Engineer Job Roles in Virginia
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Search Senior Data Science Engineer Jobs in VirginiaSenior Data Science Engineer Jobs in Virginia: Frequently Asked Questions
Which companies sponsor visas for senior data science engineers in Virginia?
Several large employers in Virginia have consistent H-1B sponsorship histories for senior data science engineers. These include Capital One, Booz Allen Hamilton, Leidos, Amazon Web Services, Accenture Federal Services, and Freddie Mac. Defense and federal contracting firms in Northern Virginia are particularly active, though sponsorship availability varies by team, project funding, and hiring cycle. Checking each employer's public LCA filings on the DOL disclosure database gives the most accurate picture of recent sponsorship activity.
Which visa types are most common for senior data science engineer roles in Virginia?
The H-1B is the most common visa category for senior data science engineers in Virginia. Because the role typically requires a bachelor's degree or higher in computer science, statistics, or a related field, it generally qualifies as a specialty occupation. Some employers, particularly large federal contractors, also sponsor L-1B visas for intracompany transferees with specialized knowledge. Candidates with extraordinary ability in machine learning or AI research may also qualify for the O-1A, though that pathway requires substantial documented achievement.
How to find senior data science engineer visa sponsorship jobs in Virginia?
Migrate Mate is built specifically for international job seekers and filters senior data science engineer roles by visa sponsorship history and location, making Virginia-specific searches straightforward. Because many Virginia employers in defense contracting and financial services require security clearances or U.S. citizenship for certain roles, it is worth filtering carefully by employer type. Migrate Mate surfaces roles from companies with verified H-1B sponsorship activity, helping you focus your applications on employers that have actually sponsored similar positions.
Which cities in Virginia have the most senior data science engineer sponsorship jobs?
Northern Virginia accounts for the largest concentration of senior data science engineer sponsorship jobs in the state. Arlington, Reston, McLean, and Tysons are home to major tech firms, federal contractors, and financial services companies that regularly hire at the senior level. Richmond is a secondary market, driven by Capital One's headquarters and a growing fintech presence. Outside these hubs, sponsorship opportunities become more limited, so candidates targeting Virginia should focus their search on the Northern Virginia corridor first.
Are there any Virginia-specific considerations for senior data science engineers seeking sponsorship?
Virginia's heavy concentration of federal contractors introduces a practical consideration: many senior data science engineer roles require security clearances, which are generally restricted to U.S. citizens or permanent residents. This narrows the pool of sponsorship-eligible positions compared to purely commercial markets. That said, the commercial technology sector in Northern Virginia, anchored by AWS's HQ2 in Arlington, has expanded significantly and includes roles that do not carry clearance requirements. Candidates should verify clearance requirements before applying to avoid spending time on ineligible positions.
What is the prevailing wage for sponsored senior data science engineer jobs in Virginia?
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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