Director Of Data Analytics Jobs in USA with Visa Sponsorship
Director of Data Analytics roles attract H-1B visa, O-1 visa, and EB-1/EB-2 sponsorship at scale. Employers regularly file LCAs for this title under SOC 15-2051, and the specialty occupation standard is straightforward to meet with a qualifying graduate degree. For detailed occupation requirements, see the O*NET profile.
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Grant Thornton is seeking a Sr. Director, Head of Data & Analytics to join the team. Approved office locations can be found below.
The Sr. Director, Head of Data & Analytics is responsible for leading the firm's enterprise Data & Analytics organization, including the strategy, delivery, governance, and operational management of the enterprise data estate. This role owns the end-to-end capability model for Data Foundations, Data Architecture, Analytics, Data Migration & Integration, and Data Governance. The organization is designed to build and operate a trusted, governed, AI-ready data foundation that enables business intelligence, reporting, analytics, data products, and enterprise AI use cases.
The Sr. Director leads a globally distributed organization responsible for building scalable data pipelines, operating enterprise data platforms, defining architecture standards, delivering business insights and reporting, executing enterprise migrations and integrations, and establishing governance practices that ensure enterprise data is trusted, consistent, discoverable, and aligned to business objectives.
The role partners closely with Enterprise Architecture, Infrastructure, Applications, Finance, Product Ownership, Integration Delivery, Information Security, Service Management, and business stakeholders to align data strategy, reporting, analytics, governance, migration, and integration priorities with enterprise objectives while maximizing business value from the firm's data assets.
Essential Duties & Responsibilities
Enterprise Data & Analytics Strategy
- Define and execute the enterprise Data & Analytics strategy, operating model, roadmap, and service delivery framework.
- Lead the Data & Analytics organization across Data Foundations, Architecture, Analytics, Migration & Integration, and Governance.
- Establish a scalable internal capability for data delivery, strengthening ownership, accountability, quality, reliability, and business outcomes.
- Partner with business, technology, product, finance, security, and operational stakeholders to align enterprise priorities with data investments and capabilities.
- Govern the portfolio of data initiatives spanning platform modernization, analytics, enterprise reporting, migration programs, AI readiness, and governance.
- Define success measures for adoption, reuse, data quality, governance maturity, compliance, and business value realization.
- Build a product-oriented operating model where enterprise data assets are reusable, governed, scalable, and business aligned.
Data Foundations & Platform Operations
- Lead the build and operation of the enterprise data foundation, including data engineering, platform operations, observability, lifecycle management, and operational governance.
- Oversee enterprise data pipelines supporting ingestion, transformation, curation, and consumption.
- Ensure the enterprise data lake and medallion architecture supports reporting, analytics, AI, and data product requirements.
- Drive DataOps practices including monitoring, orchestration, deployment, testing, lineage, SLA management, and support.
- Establish standards for reliability, performance, availability, scalability, and operational excellence.
- Enable reusable datasets and shared data assets to improve consistency and reduce duplication across the firm.
Data Architecture
- Lead enterprise data architecture, standards, and governance.
- Define the enterprise data blueprint across business domains, integrations, analytics, reporting, AI, and products.
- Establish standards for data models, domain architecture, metadata, master data, reference data, and information architecture.
- Ensure enterprise and SAP-related data structures support integrated reporting, migration, governance, analytics, and business operations.
- Partner with Enterprise Architecture to ensure data solutions align with enterprise technology standards and long-term architecture objectives.
- Govern architecture reviews, design standards, and data solution approvals.
Analytics, Reporting & Insights
- Lead delivery of enterprise reporting, dashboards, scorecards, semantic models, self-service analytics, and advanced analytics capabilities.
- Ensure trusted enterprise data is transformed into actionable business insights, operational transparency, and measurable business outcomes.
- Partner with business leadership to define KPIs, performance metrics, executive dashboards, financial reporting, client reporting, and operational insights.
- Lead enterprise reporting strategy, including operational, management, financial, executive, historical, and regulatory reporting capabilities.
- Lead SAP reporting strategy and ensure SAP reporting data aligns with enterprise definitions, governed metrics, financial hierarchies, security requirements, and reporting standards.
- Coordinate reporting integration with enterprise platforms, applications, data products, and analytics environments.
- Establish reporting standards covering certification, documentation, access management, refresh cycles, governance, and retirement.
- Ensure reporting consistency, data trust, reconciliation processes, metadata management, and common business definitions across the enterprise.
- Drive adoption and value realization of analytics and reporting products through stakeholder engagement, change management, and continuous improvement.
- Establish quality controls, data validation, auditability, and lineage practices that support executive confidence in reporting outputs.
Data Migration & Integration
- Lead enterprise data migration, conversion, integration, and cutover capabilities.
- Define migration strategies, runbooks, field mappings, harmonization rules, transformation logic, validation frameworks, reconciliation processes, and readiness criteria.
- Lead enterprise and SAP data migration programs supporting platform modernization, ERP transformation, acquisition integrations, and technology initiatives.
- Oversee profiling, cleansing, transformation, validation, reconciliation, and loading of enterprise and SAP data into target platforms.
- Ensure migration programs include mock conversions, testing cycles, cutover planning, operational readiness, business signoffs, and post-conversion stabilization.
- Partner with application teams, finance, operations, technology leaders, implementation partners, and business stakeholders to ensure successful data conversion outcomes.
- Establish reusable migration assets, utilities, transformation patterns, data mappings, conversion methodologies, and playbooks that accelerate future programs.
- Govern integration patterns spanning APIs, middleware, enterprise service buses (ESB), event-driven architectures, and point-to-point integrations.
- Ensure migrated and integrated data meets quality, compliance, reporting, operational, governance, security, and audit requirements.
Data Governance & Enterprise Trust
- Establish enterprise data governance policies, standards, business definitions, and stewardship practices.
- Define and operate the Data Owner and Data Steward model across business domains.
- Lead enterprise data quality management, metadata management, lineage, catalog, glossary, and discoverability initiatives.
- Govern data classification, retention, lifecycle management, usage standards, and access controls.
- Facilitate governance forums and decision-making bodies that align business, technology, analytics, and architecture stakeholders.
- Ensure governance practices support analytics, reporting, migration, AI, business operations, and enterprise compliance requirements.
- Drive accountability for trusted data definitions, ownership, quality, and regulatory compliance.
Leadership & Operating Model
- Build and lead a high-performing global Data & Analytics organization.
- Establish clear accountability across Data Foundations, Architecture, Analytics, Migration & Integration, and Governance functions.
- Develop future leaders and technical talent across engineering, architecture, analytics, governance, and migration disciplines.
- Create a culture focused on business value, accountability, trust, innovation, operational excellence, and measurable outcomes.
- Lead workforce planning, vendor management, financial management, investment prioritization, and capacity planning.
- Provide executive-ready communication regarding roadmap progress, migration readiness, reporting delivery, business value realization, risks, quality, compliance, and strategic investment needs.
- Partner closely with other CTO leadership functions to support enterprise transformation, AI enablement, platform modernization, and M&A integration activities.
Qualifications & Requirements
- 12+ years of progressive experience in Data & Analytics, data engineering, enterprise architecture, data migration, analytics delivery, reporting, governance, or related technology leadership roles.
- 7+ years of experience leading enterprise-scale data organizations and global delivery teams.
- Demonstrated experience building or transforming Data & Analytics organizations with responsibility for foundations, architecture, analytics, migration, and governance functions.
- Experience leading major ERP, SAP, enterprise platform, data migration, and reporting transformation initiatives.
- Strong understanding of enterprise reporting, business intelligence, semantic models, analytics platforms, KPI frameworks, and executive dashboarding.
- Experience operating enterprise data platforms including data lakes, medallion architectures, cloud data platforms, and modern analytics ecosystems.
- Experience establishing enterprise data architecture standards, governance frameworks, stewardship models, metadata management, and data quality programs.
- Experience managing large-scale migration and integration programs involving data conversion, cleansing, transformation, validation, reconciliation, testing, and cutover execution.
- Strong executive communication and stakeholder management skills.
- Ability to influence executive stakeholders and align technology investments to business outcomes.
- Bachelor's Degree in Computer Science, Information Systems, Engineering, Analytics, Business, or related field required.
- Master's Degree preferred.
PREFERRED QUALIFICATIONS
- Experience leading SAP S/4HANA, SAP ECC, ERP modernization, SAP reporting, or SAP migration programs.
- Experience with Snowflake, Microsoft Fabric, Power BI, Azure Data Services, or modern cloud data platforms.
- Experience supporting M&A integrations, platform consolidations, operating model transformations, or enterprise modernization programs.
- Experience operating within professional services, financial services, consulting, or other complex global enterprises.
- Experience building AI-ready data foundations and governed analytics ecosystems.
- Experience developing global delivery center (GDC) operating models across U.S., India, Poland, and Colombia teams.
Success Measures
- A mature enterprise Data & Analytics operating model is established with clear accountability across Foundations, Architecture, Analytics, Migration & Integration, and Governance.
- Enterprise data platforms deliver trusted, governed, AI-ready data assets that support business decisions, analytics, products, and reporting.
- Migration and integration programs are delivered with strong data quality, governance, reconciliation, business signoff, and minimal business disruption.
- Enterprise reporting provides reliable operational, financial, management, regulatory, and executive visibility.
- Data quality, governance, lineage, metadata, and stewardship capabilities demonstrate measurable improvements.
- Reporting and analytics products achieve strong adoption, trust, reuse, and business value realization.
- Data initiatives are delivered through scalable, repeatable, and governed processes that support future transformations and M&A integrations.
- Business stakeholders have confidence in enterprise data, reporting, governance, and analytics capabilities as strategic business assets.
The base salary range for this position is between $206,000 and $335,000. Placement within the pay range is at Grant Thornton’s discretion, and it is based on multiple factors, including but not limited to, job-related knowledge/skills, experience, business needs, progression within the role, geographic location, and internal equity. At Grant Thornton, compensation decisions are dependent upon the facts and circumstances of each position and candidate.
INTRODUCTION
Grant Thornton is seeking a Sr. Director, Head of Data & Analytics to join the team. Approved office locations can be found below.
The Sr. Director, Head of Data & Analytics is responsible for leading the firm's enterprise Data & Analytics organization, including the strategy, delivery, governance, and operational management of the enterprise data estate. This role owns the end-to-end capability model for Data Foundations, Data Architecture, Analytics, Data Migration & Integration, and Data Governance. The organization is designed to build and operate a trusted, governed, AI-ready data foundation that enables business intelligence, reporting, analytics, data products, and enterprise AI use cases.
The Sr. Director leads a globally distributed organization responsible for building scalable data pipelines, operating enterprise data platforms, defining architecture standards, delivering business insights and reporting, executing enterprise migrations and integrations, and establishing governance practices that ensure enterprise data is trusted, consistent, discoverable, and aligned to business objectives.
The role partners closely with Enterprise Architecture, Infrastructure, Applications, Finance, Product Ownership, Integration Delivery, Information Security, Service Management, and business stakeholders to align data strategy, reporting, analytics, governance, migration, and integration priorities with enterprise objectives while maximizing business value from the firm's data assets.
Essential Duties & Responsibilities
Enterprise Data & Analytics Strategy
- Define and execute the enterprise Data & Analytics strategy, operating model, roadmap, and service delivery framework.
- Lead the Data & Analytics organization across Data Foundations, Architecture, Analytics, Migration & Integration, and Governance.
- Establish a scalable internal capability for data delivery, strengthening ownership, accountability, quality, reliability, and business outcomes.
- Partner with business, technology, product, finance, security, and operational stakeholders to align enterprise priorities with data investments and capabilities.
- Govern the portfolio of data initiatives spanning platform modernization, analytics, enterprise reporting, migration programs, AI readiness, and governance.
- Define success measures for adoption, reuse, data quality, governance maturity, compliance, and business value realization.
- Build a product-oriented operating model where enterprise data assets are reusable, governed, scalable, and business aligned.
Data Foundations & Platform Operations
- Lead the build and operation of the enterprise data foundation, including data engineering, platform operations, observability, lifecycle management, and operational governance.
- Oversee enterprise data pipelines supporting ingestion, transformation, curation, and consumption.
- Ensure the enterprise data lake and medallion architecture supports reporting, analytics, AI, and data product requirements.
- Drive DataOps practices including monitoring, orchestration, deployment, testing, lineage, SLA management, and support.
- Establish standards for reliability, performance, availability, scalability, and operational excellence.
- Enable reusable datasets and shared data assets to improve consistency and reduce duplication across the firm.
Data Architecture
- Lead enterprise data architecture, standards, and governance.
- Define the enterprise data blueprint across business domains, integrations, analytics, reporting, AI, and products.
- Establish standards for data models, domain architecture, metadata, master data, reference data, and information architecture.
- Ensure enterprise and SAP-related data structures support integrated reporting, migration, governance, analytics, and business operations.
- Partner with Enterprise Architecture to ensure data solutions align with enterprise technology standards and long-term architecture objectives.
- Govern architecture reviews, design standards, and data solution approvals.
Analytics, Reporting & Insights
- Lead delivery of enterprise reporting, dashboards, scorecards, semantic models, self-service analytics, and advanced analytics capabilities.
- Ensure trusted enterprise data is transformed into actionable business insights, operational transparency, and measurable business outcomes.
- Partner with business leadership to define KPIs, performance metrics, executive dashboards, financial reporting, client reporting, and operational insights.
- Lead enterprise reporting strategy, including operational, management, financial, executive, historical, and regulatory reporting capabilities.
- Lead SAP reporting strategy and ensure SAP reporting data aligns with enterprise definitions, governed metrics, financial hierarchies, security requirements, and reporting standards.
- Coordinate reporting integration with enterprise platforms, applications, data products, and analytics environments.
- Establish reporting standards covering certification, documentation, access management, refresh cycles, governance, and retirement.
- Ensure reporting consistency, data trust, reconciliation processes, metadata management, and common business definitions across the enterprise.
- Drive adoption and value realization of analytics and reporting products through stakeholder engagement, change management, and continuous improvement.
- Establish quality controls, data validation, auditability, and lineage practices that support executive confidence in reporting outputs.
Data Migration & Integration
- Lead enterprise data migration, conversion, integration, and cutover capabilities.
- Define migration strategies, runbooks, field mappings, harmonization rules, transformation logic, validation frameworks, reconciliation processes, and readiness criteria.
- Lead enterprise and SAP data migration programs supporting platform modernization, ERP transformation, acquisition integrations, and technology initiatives.
- Oversee profiling, cleansing, transformation, validation, reconciliation, and loading of enterprise and SAP data into target platforms.
- Ensure migration programs include mock conversions, testing cycles, cutover planning, operational readiness, business signoffs, and post-conversion stabilization.
- Partner with application teams, finance, operations, technology leaders, implementation partners, and business stakeholders to ensure successful data conversion outcomes.
- Establish reusable migration assets, utilities, transformation patterns, data mappings, conversion methodologies, and playbooks that accelerate future programs.
- Govern integration patterns spanning APIs, middleware, enterprise service buses (ESB), event-driven architectures, and point-to-point integrations.
- Ensure migrated and integrated data meets quality, compliance, reporting, operational, governance, security, and audit requirements.
Data Governance & Enterprise Trust
- Establish enterprise data governance policies, standards, business definitions, and stewardship practices.
- Define and operate the Data Owner and Data Steward model across business domains.
- Lead enterprise data quality management, metadata management, lineage, catalog, glossary, and discoverability initiatives.
- Govern data classification, retention, lifecycle management, usage standards, and access controls.
- Facilitate governance forums and decision-making bodies that align business, technology, analytics, and architecture stakeholders.
- Ensure governance practices support analytics, reporting, migration, AI, business operations, and enterprise compliance requirements.
- Drive accountability for trusted data definitions, ownership, quality, and regulatory compliance.
Leadership & Operating Model
- Build and lead a high-performing global Data & Analytics organization.
- Establish clear accountability across Data Foundations, Architecture, Analytics, Migration & Integration, and Governance functions.
- Develop future leaders and technical talent across engineering, architecture, analytics, governance, and migration disciplines.
- Create a culture focused on business value, accountability, trust, innovation, operational excellence, and measurable outcomes.
- Lead workforce planning, vendor management, financial management, investment prioritization, and capacity planning.
- Provide executive-ready communication regarding roadmap progress, migration readiness, reporting delivery, business value realization, risks, quality, compliance, and strategic investment needs.
- Partner closely with other CTO leadership functions to support enterprise transformation, AI enablement, platform modernization, and M&A integration activities.
Qualifications & Requirements
- 12+ years of progressive experience in Data & Analytics, data engineering, enterprise architecture, data migration, analytics delivery, reporting, governance, or related technology leadership roles.
- 7+ years of experience leading enterprise-scale data organizations and global delivery teams.
- Demonstrated experience building or transforming Data & Analytics organizations with responsibility for foundations, architecture, analytics, migration, and governance functions.
- Experience leading major ERP, SAP, enterprise platform, data migration, and reporting transformation initiatives.
- Strong understanding of enterprise reporting, business intelligence, semantic models, analytics platforms, KPI frameworks, and executive dashboarding.
- Experience operating enterprise data platforms including data lakes, medallion architectures, cloud data platforms, and modern analytics ecosystems.
- Experience establishing enterprise data architecture standards, governance frameworks, stewardship models, metadata management, and data quality programs.
- Experience managing large-scale migration and integration programs involving data conversion, cleansing, transformation, validation, reconciliation, testing, and cutover execution.
- Strong executive communication and stakeholder management skills.
- Ability to influence executive stakeholders and align technology investments to business outcomes.
- Bachelor's Degree in Computer Science, Information Systems, Engineering, Analytics, Business, or related field required.
- Master's Degree preferred.
PREFERRED QUALIFICATIONS
- Experience leading SAP S/4HANA, SAP ECC, ERP modernization, SAP reporting, or SAP migration programs.
- Experience with Snowflake, Microsoft Fabric, Power BI, Azure Data Services, or modern cloud data platforms.
- Experience supporting M&A integrations, platform consolidations, operating model transformations, or enterprise modernization programs.
- Experience operating within professional services, financial services, consulting, or other complex global enterprises.
- Experience building AI-ready data foundations and governed analytics ecosystems.
- Experience developing global delivery center (GDC) operating models across U.S., India, Poland, and Colombia teams.
Success Measures
- A mature enterprise Data & Analytics operating model is established with clear accountability across Foundations, Architecture, Analytics, Migration & Integration, and Governance.
- Enterprise data platforms deliver trusted, governed, AI-ready data assets that support business decisions, analytics, products, and reporting.
- Migration and integration programs are delivered with strong data quality, governance, reconciliation, business signoff, and minimal business disruption.
- Enterprise reporting provides reliable operational, financial, management, regulatory, and executive visibility.
- Data quality, governance, lineage, metadata, and stewardship capabilities demonstrate measurable improvements.
- Reporting and analytics products achieve strong adoption, trust, reuse, and business value realization.
- Data initiatives are delivered through scalable, repeatable, and governed processes that support future transformations and M&A integrations.
- Business stakeholders have confidence in enterprise data, reporting, governance, and analytics capabilities as strategic business assets.
The base salary range for this position is between $206,000 and $335,000. Placement within the pay range is at Grant Thornton’s discretion, and it is based on multiple factors, including but not limited to, job-related knowledge/skills, experience, business needs, progression within the role, geographic location, and internal equity. At Grant Thornton, compensation decisions are dependent upon the facts and circumstances of each position and candidate.
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Get Access To All JobsTips for Finding Director Of Data Analytics Jobs
Target companies with LCA filing history
Employers who have previously filed Labor Condition Applications for data analytics directors are far more likely to sponsor again. DOL disclosure data shows which companies have sponsored this exact title, saving you time targeting dead ends.
Lead with your graduate degree upfront
H-1B specialty occupation approval for this role is strongest with a master's or PhD in statistics, computer science, or a quantitative field. Listing your degree prominently on your resume signals immediate eligibility and reduces employer hesitation around sponsorship risk.
Position yourself as an O-1 candidate if you qualify
Directors with published research, industry awards, or media coverage may qualify for O-1A status, which has no lottery and no annual cap. Frame your career narrative around measurable impact and recognition rather than job duties alone.
Address sponsorship directly in your cover letter
Employers often hesitate because they assume sponsorship is complicated. A brief, confident sentence explaining the process, typical timeline, and that H-1B transfer costs are modest can remove that objection before your application reaches a recruiter's desk.
Focus on large enterprises and mature tech companies
Fortune 500 companies, large financial institutions, and established technology firms have dedicated immigration counsel and routine sponsorship workflows. They sponsor Director of Data Analytics roles regularly and are less deterred by the process than smaller organizations.
Pursue EB-2 NIW if you have a research or policy angle
Directors whose work has national implications, such as healthcare analytics, public sector data infrastructure, or AI policy, may self-petition under EB-2 National Interest Waiver without employer sponsorship, offering a parallel green card path alongside your job search.
Frequently Asked Questions
Is Director of Data Analytics a qualifying specialty occupation for H-1B?
Yes. The role consistently qualifies as a specialty occupation under H-1B visa because it normally requires at least a bachelor's degree in a specific technical field such as statistics, computer science, or applied mathematics. USCIS has approved this title at high rates when petitions document the theoretical and practical application of that degree. A generic business or liberal arts background without quantitative coursework creates risk, so degree alignment matters.
What degree do I need for an employer to sponsor me in this role?
Most employers require a master's degree in data science, statistics, computer science, or a closely related quantitative discipline for director-level roles. A bachelor's in one of those fields combined with progressive experience can work, but graduate credentials significantly strengthen the H-1B petition and reduce the risk of an USCIS Request for Evidence. Some employers also accept equivalent experience under the three-for-one substitution rule.
How do I find Director of Data Analytics jobs that offer visa sponsorship?
Migrate Mate filters job listings specifically for roles offering visa sponsorship, so you're not wasting time applying to companies that won't consider international candidates. The platform surfaces employers with active LCA filings and sponsorship history for this title, which is a strong signal that the hiring team is already equipped to handle the process.
Can I transfer my H-1B to a new employer for this role without losing status?
Yes. H-1B portability lets you start working for a new employer as soon as they file a transfer petition, as long as you're maintaining valid status and your prior petition was approved. For Director of Data Analytics roles, the new employer files a fresh I-129 with an updated LCA reflecting the new position. You don't need to restart the cap count or re-enter the lottery.
Does the H-1B lottery affect my chances of getting sponsored for this role?
If you're currently outside the U.S. and need a new H-1B, yes, the annual lottery applies and selection isn't guaranteed. However, if you're already in H-1B status, a transfer to a new employer is cap-exempt. Candidates on F-1 OPT or STEM OPT can work while their sponsoring employer enters them in the next lottery. O-1A is an alternative that bypasses the lottery entirely for candidates with documented recognition.
What is the prevailing wage requirement for sponsored Director Of Data Analytics 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.