Analytics Engineer Jobs at Deloitte with Visa Sponsorship
Deloitte hires Analytics Engineers across its consulting and technology practices, working on data pipeline architecture, dbt modeling, and cloud analytics platforms for enterprise clients. The firm has an established visa sponsorship infrastructure and regularly files petitions for qualified international candidates in this function.
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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 Analytics Engineer Jobs at Deloitte Jobs
Align your portfolio to Deloitte's tech stack
Deloitte's Analytics Engineer roles center on dbt, Snowflake, and cloud platforms like AWS and Azure. Recruiters screen for hands-on project experience with these tools, so surface that work explicitly in your resume before applying.
Target Deloitte's federal and commercial practices separately
Deloitte splits into distinct business units with different hiring timelines. Federal consulting roles often require security clearance eligibility, which can complicate sponsorship. Commercial practice openings are typically more accessible for candidates needing H-1B or E-3 support.
Find open Analytics Engineer roles using Migrate Mate
Deloitte posts Analytics Engineer openings across multiple practices and locations simultaneously. Use Migrate Mate to filter specifically for roles flagged for visa sponsorship so you're only applying where a petition pathway is already in play.
Confirm LCA coverage before your final interview round
Deloitte files Labor Condition Applications with the DOL for each work location, not just a single national posting. If your target office differs from where the role was advertised, ask your recruiter whether a separate LCA will be filed for that site.
Time your application around Deloitte's campus recruiting cycle
Deloitte runs a structured campus recruiting calendar that frontloads offer decisions ahead of the H-1B registration window in March. Applying through campus channels in the fall gives your petition the best chance of being included in that cycle.
Clarify premium processing availability during offer negotiation
USCIS premium processing reduces H-1B adjudication to 15 business days. Deloitte's sponsorship team handles this on a case-by-case basis, so confirm during the offer stage whether it applies to your petition rather than assuming it's standard.
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Find Analytics Engineer at Deloitte JobsFrequently Asked Questions
Does Deloitte sponsor H-1B visas for Analytics Engineers?
Yes, Deloitte sponsors H-1B visas for Analytics Engineers. The firm has an established immigration team that manages petitions across its consulting and technology practices. Sponsorship is generally available for full-time roles where the position qualifies as a specialty occupation, which Analytics Engineer roles typically do given their degree and technical requirements.
Which visa types does Deloitte commonly sponsor for Analytics Engineer roles?
Deloitte sponsors H-1B, H-1B1, and E-3 visas for Analytics Engineer positions, covering candidates from most countries as well as Australians and Singaporeans through their dedicated visa categories. For longer-term pathways, Deloitte also supports EB-2 and EB-3 Green Card sponsorship, though that process typically begins after you've been with the firm for some time.
What qualifications and experience does Deloitte expect for Analytics Engineer roles?
Deloitte generally looks for a bachelor's degree in computer science, information systems, statistics, or a related field. Practical experience with data transformation tools like dbt, query languages like SQL, and cloud data warehouses such as Snowflake or BigQuery is expected. Consulting-specific experience or client-facing project work strengthens your profile significantly compared to purely technical backgrounds.
How do I apply for Analytics Engineer jobs at Deloitte?
You can apply directly through Deloitte's careers portal or through Migrate Mate, which filters Deloitte's Analytics Engineer openings specifically by visa sponsorship eligibility so you're not wasting applications on roles that won't support a petition. Deloitte's hiring process typically includes a recruiter screen, technical assessments, and multiple rounds of case or behavioral interviews before an offer is extended.
How do I plan my timeline if I need Deloitte to file an H-1B petition?
The H-1B cap registration window opens in March each year, with selections made shortly after and approved petitions taking effect October 1. If you're targeting this cycle, you'll need an offer finalized and paperwork submitted to Deloitte's immigration team well before March. If you're already in H-1B status with another employer, Deloitte can file a transfer petition outside the cap, which has more flexibility on timing.
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