Data Engineer Jobs at Deloitte with Visa Sponsorship
Deloitte hires Data Engineers across its consulting, analytics, and federal practices, working on client-facing data infrastructure, cloud pipelines, and platform modernization. The company has an established visa sponsorship process for this function and works with candidates on H-1B, E-3, and Green Card pathways.
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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
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Get Access To All JobsTips for Finding Data Engineer Jobs at Deloitte Jobs
Align your credentials with Deloitte's specialty occupation standard
Deloitte submits H-1B petitions under the specialty occupation standard, which requires your degree to directly relate to data engineering work. A computer science, information systems, or engineering degree maps cleanly. A business degree with no technical coursework creates risk at USCIS adjudication.
Target roles inside Deloitte's federal and cloud practices
Deloitte's Government and Public Services practice and cloud-focused platforms like Deloitte Cloud run large data engineering engagements. These teams have consistent headcount needs and structured onboarding timelines that align better with H-1B cap filing windows than project-based commercial consulting roles.
Search Deloitte's open Data Engineer positions on Migrate Mate
Filter specifically for Deloitte Data Engineer openings on Migrate Mate to see which positions are active and visa-sponsorship eligible. This saves time that would otherwise go to sorting through postings where sponsorship isn't confirmed.
Confirm your visa category early in the interview process
Deloitte sponsors multiple visa types for Data Engineers, including H-1B, E-3 for Australian citizens, and H-1B1 for Chilean and Singaporean nationals. Clarifying your eligibility category with the recruiter before offer stage prevents last-minute filing complications and sets accurate start date expectations.
Time your application around the H-1B cap registration window
USCIS opens H-1B cap registration in March each year, with October 1 as the earliest possible start date. If you're interviewing at Deloitte in late spring or summer, discuss a cap-exempt bridge option or a deferred start to avoid a year-long gap in work authorization.
Prepare for Deloitte's technical and client-readiness interview format
Deloitte Data Engineer interviews typically include SQL and cloud architecture components alongside behavioral questions about client delivery. Having documented project experience with platforms like AWS, Azure, or Snowflake strengthens both your candidacy and the specialty occupation argument in your visa petition.
Data Engineer at Deloitte jobs are hiring across the US. Find yours.
Find Data Engineer at Deloitte JobsFrequently Asked Questions
Does Deloitte sponsor H-1B visas for Data Engineers?
Yes, Deloitte sponsors H-1B visas for Data Engineers and is one of the more active sponsors in the consulting sector for this role. Sponsorship is tied to specific positions rather than guaranteed at application, so confirming sponsorship availability with your recruiter before the offer stage is the most reliable approach.
How do I apply for Data Engineer jobs at Deloitte?
Apply through Deloitte's careers portal at deloitte.com/careers, or browse verified sponsorship-eligible Data Engineer openings at Deloitte on Migrate Mate. Tailoring your resume to reflect cloud platforms, data pipeline tools, and client delivery experience increases your chances of passing Deloitte's initial screening for this function.
Which visa types does Deloitte commonly use for Data Engineer roles?
Deloitte sponsors H-1B, H-1B1, and E-3 visas for Data Engineers, as well as employer-sponsored Green Card pathways including EB-2 and EB-3. The right visa category depends on your nationality and qualifications. Australian citizens can pursue the E-3, which has no lottery, while most other nationalities go through the H-1B cap process.
What qualifications does Deloitte expect from Data Engineer candidates seeking sponsorship?
Deloitte typically looks for a bachelor's degree or higher in computer science, information systems, or a related technical field, plus hands-on experience with cloud data platforms such as AWS, Azure, or GCP, and tools like Spark, dbt, or SQL. For USCIS specialty occupation purposes, the degree must be directly relevant to the specific role being offered.
How do I handle timing if I need Deloitte to sponsor my H-1B?
H-1B employment at Deloitte can begin no earlier than October 1 following the March registration window. If you receive an offer outside that window, discuss whether the role qualifies for cap-exempt filing or whether a deferred start is feasible. The 60-day grace period after a prior job ends still applies, so plan your timeline accordingly with USCIS deadlines in mind.
See which Data Engineer at Deloitte employers are hiring and sponsoring visas right now.
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