Data Science Engineer Jobs at Deloitte with Visa Sponsorship
Deloitte hires Data Science Engineers across consulting practices, analytics platforms, and client delivery teams, and the firm has a well-established infrastructure for sponsoring work visas across multiple categories. If you need sponsorship, Deloitte is one of the more predictable large employers to target in professional services.
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Get Access To All JobsAI Data Engineer - Manager
Our Human Capital practice is at the forefront of transforming the nature of work. As converging forces reshape industries, our team uniquely addresses the complexities of work, workforce, and workplace dynamics. We leverage sector-specific insights and cross-domain perspectives to help organizations tackle their most challenging workforce issues and align talent strategies with their strategic visions. Our practice is renowned for making work better for humans and humans better at work. Be part of this exciting era of change and join us on this transformative journey.
Recruiting for this role ends on August 30, 2026
Work You'll Do:
The AI Data Engineer will lead the data architecture and engineering delivery that enables AI/ML/GenAI solutions, ensuring data is trusted, secure, observable, and scalable from ingestion through consumption. You will design and operationalize modern data and retrieval foundations to support LLM-powered applications (e.g., Claude, GPT/Codex, Gemini) including patterns such as RAG, embeddings, vector search, and governed access to structured and unstructured data. You will manage day-to-day delivery with an onshore/offshore team, partnering with data science, ML engineering, and product stakeholders to translate use cases into production-ready pipelines and platforms with strong data governance, lineage, quality controls, and monitoring. This role blends hands-on technical leadership with delivery management and team development, driving consistent engineering standards and measurable outcomes in client environments.
Strategic Alignment and Vision
Help define the AI/ML/GenAI technical direction and vision, ensuring alignment with strategic goals and digital transformation efforts.
Translate the vision of business leaders into realistic technical implementations, while identifying misaligned initiatives and impractical use cases
Architectural Design
* Design end-to-end AI architectures, from data ingestion to model deployment, integrating with cloud and on-premises systems.
Design and Technology Selection
Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage machine learning models and large language models.
Research and Development
Conduct research to provide technical solutions to scale AI/ML powered features for real-world challenges, making trade-offs based on quality, scalability, performance, and cost.
Lead the development of AI models (e.g., machine learning, natural language processing, computer vision) and implement scalable AI solutions.
Collaboration and Stakeholder Engagement
Collaborate with Enterprise, Application, Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design.
Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements.
Consulting & Advisory
* Serve as a technical advisor to leadership, providing insights on AI trends, potential business impacts, and implementation best practices.
Operational Excellence and Continuous Improvement
Be responsible for the successful execution of AI-powered applications using agile methodology.
Audit AI tools and practices across data, models and software engineering, focusing on continuous improvement and feedback mechanisms.
* Contribute to standardizing CI/CD pipelines, user and service roles, and container creation, model consumption, testing, and deployment methodology based on business and security requirements.
Risk Management and Ethical Considerations
Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
Product Strategy and Business Understanding
Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
Break down client problems and bring an understanding of leading technology, analytics methods, tools, and operating model approaches.
Tool Development and Data Management
Build tools and capabilities that assist with data ingestion, feature engineering, data management, and organization.
Design, implement, and maintain distributed computing solutions for data processing and model training, ensuring the security, scalability, and reliability of machine learning infrastructure.
The Team
Our Insights, Innovation & Operate Offering is designed to enhance key aspects of our clients' businesses by leveraging cutting-edge technology, data, and a blend of deep technical and human expertise. We innovate and deliver creative, industry-specific solutions that streamline operations and accelerate speed-to-value.
Required Qualifications:
Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems or related field.
6+ years of consulting experience leading delivery teams, including onshore and offshore team members
6+ years of experience gathering non-functional requirements and defining application architecture frameworks, including validation and testing deliverables
5+ years of experience working in an AI environment
5+ years of experience translating requirements into client ready design documents
5+ years of experience in software application architecture analysis, design, and delivery
5+ years of experience executing full system development life cycle implementations
Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
* Limited immigration sponsorship may be available.
Preferred Qualifications:
Advanced degrees such as Masters or PhD are preferred
Certifications in AI/ML technologies and Cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect
5+ years of experience in Data Science, Statistics, and Machine Learning
5+ years of experience in Generative AI/LLMs, preferably experienced in delivering and productionizing
5+ years of experience in machine learning model development, natural language processing, and data analysis; Experienced in Supervised and Unsupervised learning, feature engineering, model training, and deployment
5+ year of experience in implementing cloud-based AI/ML workloads on any of AWS, Microsoft and Azure.
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $130,800-241,000.
Possible Locations:
Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dallas, Denver, Detroit, Hartford, Houston, Indianapolis, Jacksonville, Kansas City, Las Vegas, Los Angeles, McLean, Miami, Milwaukee, Nashville, New Orleans, New York, Philadelphia, Pittsburgh, Portland, Raleigh, Richmond, Sacramento, San Antonio, San Diego, San Francisco, San Jose, Seattle, St. Louis, Stamford, Tampa, Tempe
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
For more information about Human Capital, visit our landing page at: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-human-capital-consulting-jobs.html
HCFY26 #IIOFY26
AI Data Engineer - Manager
Our Human Capital practice is at the forefront of transforming the nature of work. As converging forces reshape industries, our team uniquely addresses the complexities of work, workforce, and workplace dynamics. We leverage sector-specific insights and cross-domain perspectives to help organizations tackle their most challenging workforce issues and align talent strategies with their strategic visions. Our practice is renowned for making work better for humans and humans better at work. Be part of this exciting era of change and join us on this transformative journey.
Recruiting for this role ends on August 30, 2026
Work You'll Do:
The AI Data Engineer will lead the data architecture and engineering delivery that enables AI/ML/GenAI solutions, ensuring data is trusted, secure, observable, and scalable from ingestion through consumption. You will design and operationalize modern data and retrieval foundations to support LLM-powered applications (e.g., Claude, GPT/Codex, Gemini) including patterns such as RAG, embeddings, vector search, and governed access to structured and unstructured data. You will manage day-to-day delivery with an onshore/offshore team, partnering with data science, ML engineering, and product stakeholders to translate use cases into production-ready pipelines and platforms with strong data governance, lineage, quality controls, and monitoring. This role blends hands-on technical leadership with delivery management and team development, driving consistent engineering standards and measurable outcomes in client environments.
Strategic Alignment and Vision
Help define the AI/ML/GenAI technical direction and vision, ensuring alignment with strategic goals and digital transformation efforts.
Translate the vision of business leaders into realistic technical implementations, while identifying misaligned initiatives and impractical use cases
Architectural Design
* Design end-to-end AI architectures, from data ingestion to model deployment, integrating with cloud and on-premises systems.
Design and Technology Selection
Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage machine learning models and large language models.
Research and Development
Conduct research to provide technical solutions to scale AI/ML powered features for real-world challenges, making trade-offs based on quality, scalability, performance, and cost.
Lead the development of AI models (e.g., machine learning, natural language processing, computer vision) and implement scalable AI solutions.
Collaboration and Stakeholder Engagement
Collaborate with Enterprise, Application, Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot use cases and discuss best design.
Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements.
Consulting & Advisory
* Serve as a technical advisor to leadership, providing insights on AI trends, potential business impacts, and implementation best practices.
Operational Excellence and Continuous Improvement
Be responsible for the successful execution of AI-powered applications using agile methodology.
Audit AI tools and practices across data, models and software engineering, focusing on continuous improvement and feedback mechanisms.
* Contribute to standardizing CI/CD pipelines, user and service roles, and container creation, model consumption, testing, and deployment methodology based on business and security requirements.
Risk Management and Ethical Considerations
Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
Product Strategy and Business Understanding
Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
Break down client problems and bring an understanding of leading technology, analytics methods, tools, and operating model approaches.
Tool Development and Data Management
Build tools and capabilities that assist with data ingestion, feature engineering, data management, and organization.
Design, implement, and maintain distributed computing solutions for data processing and model training, ensuring the security, scalability, and reliability of machine learning infrastructure.
The Team
Our Insights, Innovation & Operate Offering is designed to enhance key aspects of our clients' businesses by leveraging cutting-edge technology, data, and a blend of deep technical and human expertise. We innovate and deliver creative, industry-specific solutions that streamline operations and accelerate speed-to-value.
Required Qualifications:
Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems or related field.
6+ years of consulting experience leading delivery teams, including onshore and offshore team members
6+ years of experience gathering non-functional requirements and defining application architecture frameworks, including validation and testing deliverables
5+ years of experience working in an AI environment
5+ years of experience translating requirements into client ready design documents
5+ years of experience in software application architecture analysis, design, and delivery
5+ years of experience executing full system development life cycle implementations
Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
* Limited immigration sponsorship may be available.
Preferred Qualifications:
Advanced degrees such as Masters or PhD are preferred
Certifications in AI/ML technologies and Cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer, Azure Data Scientist, or Azure Solutions Architect
5+ years of experience in Data Science, Statistics, and Machine Learning
5+ years of experience in Generative AI/LLMs, preferably experienced in delivering and productionizing
5+ years of experience in machine learning model development, natural language processing, and data analysis; Experienced in Supervised and Unsupervised learning, feature engineering, model training, and deployment
5+ year of experience in implementing cloud-based AI/ML workloads on any of AWS, Microsoft and Azure.
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $130,800-241,000.
Possible Locations:
Atlanta, Austin, Baltimore, Boston, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Costa Mesa, Dallas, Denver, Detroit, Hartford, Houston, Indianapolis, Jacksonville, Kansas City, Las Vegas, Los Angeles, McLean, Miami, Milwaukee, Nashville, New Orleans, New York, Philadelphia, Pittsburgh, Portland, Raleigh, Richmond, Sacramento, San Antonio, San Diego, San Francisco, San Jose, Seattle, St. Louis, Stamford, Tampa, Tempe
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
For more information about Human Capital, visit our landing page at: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-human-capital-consulting-jobs.html
HCFY26 #IIOFY26
See all 271+ Data Science Engineer at Deloitte jobs
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Get Access To All JobsTips for Finding Data Science Engineer Jobs at Deloitte Jobs
Align Your Portfolio to Client Delivery Work
Deloitte's Data Science Engineer roles sit inside client-facing practices, not pure product teams. Showcase projects where you translated data models into business outcomes for external stakeholders, not just internal tooling or research work.
Target Roles Inside Deloitte's AI and Analytics Offerings
Deloitte staffs Data Science Engineers heavily through its AI and Analytics practice. Filtering applications to roles within that practice increases your odds of landing on a team with established visa sponsorship workflows and experienced HR coordinators.
Clarify Visa Category Eligibility Before Applying
Deloitte sponsors H-1B, E-3, and Green Card pathways, but not every role triggers every category. If you hold Australian citizenship, confirm E-3 eligibility early since the process runs through consular processing and has a separate timeline from H-1B filing.
Prepare for a Multi-Round Technical Interview Process
Deloitte's Data Science Engineer interviews typically include a case component tied to consulting methodology alongside technical assessments. Have documented examples of deploying models in production environments, not just exploratory analysis, ready before your first screen.
Confirm LCA Filing Before Accepting Any Offer
Before signing an offer, ask the recruiting team to confirm a Labor Condition Application will be filed with DOL. For H-1B hires outside cap-exempt categories, this step must precede USCIS petition submission, and delays here can compress your start date window.
Use Migrate Mate to Prioritize Your Applications
Data Science Engineer openings at large consulting firms move quickly and vary by sponsorship type. Use Migrate Mate to filter Deloitte listings by the visa categories you qualify for, so you focus your effort on roles where sponsorship is confirmed.
Data Science Engineer at Deloitte jobs are hiring across the US. Find yours.
Find Data Science Engineer at Deloitte JobsFrequently Asked Questions
Does Deloitte sponsor H-1B visas for Data Science Engineers?
Yes, Deloitte sponsors H-1B visas for Data Science Engineers and has done so consistently across its consulting and analytics practices. The process typically involves Deloitte's internal immigration team coordinating with external counsel. Because Deloitte is a large employer subject to the standard H-1B cap, new hires requiring initial H-1B status must go through the annual lottery, which opens in March for an October 1 start date.
How do I apply for Data Science Engineer jobs at Deloitte?
Applications go through Deloitte's careers portal, but roles fill quickly and requisitions are often tied to specific practice areas. Use Migrate Mate to surface active Data Science Engineer listings at Deloitte filtered by your visa type, then apply directly through the official Deloitte portal. Tailor your application to the specific practice, whether that is AI and Analytics, Government and Public Services, or another business unit.
Which visa types does Deloitte commonly use for Data Science Engineers?
Deloitte sponsors H-1B and H-1B1 visas for most international Data Science Engineers, along with the E-3 for Australian citizens. For longer-term pathways, Deloitte also supports EB-2 and EB-3 Green Card sponsorship, often initiated after a period of employment. The visa category pursued depends on your nationality, degree level, and the specific role's classification under USCIS specialty occupation criteria.
What qualifications does Deloitte expect for Data Science Engineer roles?
Most Data Science Engineer roles at Deloitte require a bachelor's or master's degree in computer science, statistics, applied mathematics, or a closely related field. Practical experience with machine learning pipelines, cloud platforms such as AWS or Azure, and data engineering tools like Spark or Databricks is expected. Roles tied to client delivery also value experience communicating technical findings to non-technical audiences, which is a differentiator in consulting environments.
How do I manage the timeline between an offer and my visa start date at Deloitte?
For H-1B hires, Deloitte typically targets an October 1 start date aligned with the federal fiscal year cap. If you receive an offer before the March lottery window, expect a gap of six or more months between offer acceptance and your legal start date. E-3 applicants generally move faster since there's no lottery and consular appointments in Australia currently run within a few weeks. Confirm the specific timeline with your Deloitte recruiter early in the process.
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