HR Analyst Jobs at Deloitte with Visa Sponsorship
HR Analyst jobs at Deloitte span its consulting and advisory practices, supporting workforce strategy, talent operations, and people analytics. The firm has a strong track record of sponsoring work visas for this function, making it a realistic target if you're building a U.S. career in human resources.
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Get Access To All JobsAre you an experienced, passionate pioneer in data and technology who wants to work in a collaborative environment? As an experienced Senior Data Product Analyst - Data Management Engineer III, you will have the opportunity to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model tailored specifically for long-term, onsite client service delivery.
Recruiting for this role ends on: September 10th, 2026
Work you'll do / Responsibilities
You will support a Data & Analytics Foundry operating across numerous business product teams in a scaled staff augmentation model, serving as a senior data product and analytics resource across the Media Network analytics framework.
- Lead the identification, documentation, and prioritization of gaps in existing data products that cause delays, inefficiencies, inconsistent measurement, or limitations for business users.
- Translate identified gaps into a centralized intake process, prioritized backlog, delivery roadmap, and actionable resolution plans.
- Partner across pods, business product teams, domain data leaders, product managers, engineers, analysts, data scientists, and business stakeholders to align priorities, dependencies, and delivery timelines.
- Coordinate shared resources and cross-functional contributors to address data product issues efficiently and effectively.
- Act as a senior cross-pod connector to drive representation, alignment, decision-making, and consensus across product, data, engineering, analytics, and business teams.
- Elevate point solutions into scalable, reusable, governed, and discoverable data products that improve measurement consistency and reduce duplication.
- Define and maintain data product requirements, user needs, product objectives, success metrics, adoption KPIs, acceptance criteria, and operational performance indicators.
- Conduct product experiments, stakeholder interviews, user research, and feedback analysis to better understand data consumption patterns, user needs, and feature requirements.
- Prioritize enhancements and product features based on business value, user demand, feasibility, dependencies, risk, and expected impact.
- Document and maintain data product roadmaps, release plans, product requirements, operational support requirements, and product documentation.
- Analyze and measure product performance, data usability, data quality, adoption, discoverability, accessibility, and business value to inform product decisions.
- Partner with engineering, QA, analytics, and business stakeholders to deliver iterative improvements and validate product readiness.
- Apply advanced SQL to query, analyze, profile, and validate data; investigate data issues; and assess data product quality and performance.
- Use Python, as appropriate, to support data analysis, automation, validation, data quality checks, and product insights.
- Apply knowledge of data modeling, BI, semantic layers, and metrics layers to support effective data product design and analytics enablement.
- Support the design and adoption of reusable data products, governed data services, semantic layers, metrics layers, data models, and structured data services.
- Support governance, metadata, cataloging, lineage, access control, privacy, security, and documentation standards to improve transparency, usability, and trust in data products.
- Define and maintain common business definitions, data elements, metrics, ownership models, and quality expectations across business product teams.
- Support the delivery of trusted data products for BI reporting, dashboards, advanced analytics, machine learning, generative AI, and other data-driven use cases.
- Collaborate with data engineering teams using modern data engineering patterns and orchestration technologies such as Spark, Airflow, dbt, or equivalent tools.
- Lead backlog refinement, sprint planning, prioritization, dependency management, release coordination, and delivery tracking for assigned data product workstreams.
- Coordinate work across onshore and offshore delivery teams, including shared resources supporting the Data & Analytics Foundry operating model.
- Prepare product roadmaps, requirements documentation, process flows, status reports, demonstrations, executive briefings, and stakeholder-ready narratives.
- Translate complex data architecture, data engineering, analytics, and AI concepts into clear business requirements, product strategies, and implementation priorities.
- Build consensus across stakeholders when data definitions, product priorities, implementation approaches, or delivery timelines differ.
- Provide clear guidance to others.
- Mentor analysts and other delivery professionals on data product management, data analysis, data quality, governance, and stakeholder engagement.
- Communicate regularly with Engagement Managers, project team members, and representatives from various functional and/or technical teams, including escalating any matters that require additional attention and consideration from engagement management.
- Independently and collaboratively lead client engagement workstreams focused on improving analytics capabilities, resolving delivery bottlenecks, and driving operational outcomes.
- Meticulous attention to detail and quality of work product.
- Ability to build and sustain professional relationships.
- Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment.
- Strong interpersonal skills and professional demeanor.
- Ability to meet deadlines.
The Team
AI & Data - AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated solutions across software, data, AI, networks, and cloud infrastructure. These solutions are powered by engineering for business advantage, helping transform mission-critical operations. Our teams enable clients to modernize technology and data platforms while delivering scalable, high-value outcomes tailored to their business needs.
Qualifications
Required
- Bachelor's degree in computer science, Engineering, Data Science, Information Systems, Analytics, or a related field, or equivalent practical experience.
- 6+ years of experience across data product management, data product analysis, data engineering, analytics engineering, BI/reporting, data science, data governance, or related technical roles.
- 3+ years of experience supporting data product, AI/ML, generative AI, advanced analytics, or data-driven transformation initiatives.
- 6+ years of experience working with data products, data analysis, data engineering, analytics, or related data and technology capabilities.
- Advanced proficiency in SQL, including complex joins, common table expressions, window functions, data profiling, data validation, and analytical query development.
- Experience with data engineering patterns and at least 1 processing, transformation, or orchestration technology such as Spark, Airflow, dbt, or equivalent.
- Demonstrated experience building, managing, or delivering enterprise data products, semantic layers, metrics layers, data models, governed APIs, or reusable structured data services.
- Working knowledge of data governance, metadata management, data cataloging, data lineage, data quality, access control, privacy, security, and compliance practices.
- Experience gathering, analyzing, and documenting business, technical, and data product requirements.
- Experience defining product success metrics, user adoption KPIs, acceptance criteria, operational indicators, and measurable business outcomes.
- Experience evaluating data usability, quality, discoverability, accessibility, timeliness, and business value.
- Limited immigration sponsorship may be available.
- Ability to travel up to 10%, on average, based on project and client needs.
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 $107,900.00 to $179,900.00.
Preferred
- Experience using Python for data analysis, automation, data validation, data quality, or data engineering use cases.
- Experience with BI and reporting platforms, enterprise dashboards, governed metrics, or self-service analytics.
- Working knowledge of knowledge graphs, graph-based data models, entity resolution, or relationship-oriented data products.
- Experience with cloud data platforms and modern data ecosystems, such as Snowflake, Databricks, Microsoft Azure, AWS, or Google Cloud.
- Experience with data catalog, governance, metadata, or data quality platforms such as Collibra, Alation, Informatica, Microsoft Purview, or equivalent tools.
- Experience supporting AI/ML or generative AI solutions through trusted datasets, governed data products, reusable features, or responsible data practices.
- Experience working in cross-functional product, analytics, engineering, and QA environments.
- Experience conducting product experiments, user research, stakeholder interviews, or market research.
- Experience maintaining data product roadmaps, release plans, product backlogs, and operational support models.
- Agile delivery experience, including backlog management, sprint planning, release planning, and dependency tracking.
- Experience working in a staff augmentation, delivery center, shared services, or product-aligned operating model.
- Ability to manage multiple priorities and stakeholders with minimal supervision.
Benefits
At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Deloitte can mean for you.
Recruiting tips
From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters.
Our people and culture
Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work.
Our purpose
Deloitte's purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Learn more.
Professional development
From entry-level employees to senior leaders, we believe there's always room to learn. We offer opportunities to build new skills, take on leadership opportunities and connect and grow through mentorship. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career.
Qualified applicants with criminal histories, including arrest or conviction records, will be considered for employment in accordance with the requirements of applicable state and local laws, including the Los Angeles County Fair Chance Ordinance for Employers, City of Los Angeles's Fair Chance Initiative for Hiring Ordinance, San Francisco Fair Chance Ordinance, and the California Fair Chance Act. See notices of various fair chance hiring and ban-the-box laws where available. Fair Chance Hiring and Ban-the-Box Notices - Deloitte US Careers
Are you an experienced, passionate pioneer in data and technology who wants to work in a collaborative environment? As an experienced Senior Data Product Analyst - Data Management Engineer III, you will have the opportunity to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model tailored specifically for long-term, onsite client service delivery.
Recruiting for this role ends on: September 10th, 2026
Work you'll do / Responsibilities
You will support a Data & Analytics Foundry operating across numerous business product teams in a scaled staff augmentation model, serving as a senior data product and analytics resource across the Media Network analytics framework.
- Lead the identification, documentation, and prioritization of gaps in existing data products that cause delays, inefficiencies, inconsistent measurement, or limitations for business users.
- Translate identified gaps into a centralized intake process, prioritized backlog, delivery roadmap, and actionable resolution plans.
- Partner across pods, business product teams, domain data leaders, product managers, engineers, analysts, data scientists, and business stakeholders to align priorities, dependencies, and delivery timelines.
- Coordinate shared resources and cross-functional contributors to address data product issues efficiently and effectively.
- Act as a senior cross-pod connector to drive representation, alignment, decision-making, and consensus across product, data, engineering, analytics, and business teams.
- Elevate point solutions into scalable, reusable, governed, and discoverable data products that improve measurement consistency and reduce duplication.
- Define and maintain data product requirements, user needs, product objectives, success metrics, adoption KPIs, acceptance criteria, and operational performance indicators.
- Conduct product experiments, stakeholder interviews, user research, and feedback analysis to better understand data consumption patterns, user needs, and feature requirements.
- Prioritize enhancements and product features based on business value, user demand, feasibility, dependencies, risk, and expected impact.
- Document and maintain data product roadmaps, release plans, product requirements, operational support requirements, and product documentation.
- Analyze and measure product performance, data usability, data quality, adoption, discoverability, accessibility, and business value to inform product decisions.
- Partner with engineering, QA, analytics, and business stakeholders to deliver iterative improvements and validate product readiness.
- Apply advanced SQL to query, analyze, profile, and validate data; investigate data issues; and assess data product quality and performance.
- Use Python, as appropriate, to support data analysis, automation, validation, data quality checks, and product insights.
- Apply knowledge of data modeling, BI, semantic layers, and metrics layers to support effective data product design and analytics enablement.
- Support the design and adoption of reusable data products, governed data services, semantic layers, metrics layers, data models, and structured data services.
- Support governance, metadata, cataloging, lineage, access control, privacy, security, and documentation standards to improve transparency, usability, and trust in data products.
- Define and maintain common business definitions, data elements, metrics, ownership models, and quality expectations across business product teams.
- Support the delivery of trusted data products for BI reporting, dashboards, advanced analytics, machine learning, generative AI, and other data-driven use cases.
- Collaborate with data engineering teams using modern data engineering patterns and orchestration technologies such as Spark, Airflow, dbt, or equivalent tools.
- Lead backlog refinement, sprint planning, prioritization, dependency management, release coordination, and delivery tracking for assigned data product workstreams.
- Coordinate work across onshore and offshore delivery teams, including shared resources supporting the Data & Analytics Foundry operating model.
- Prepare product roadmaps, requirements documentation, process flows, status reports, demonstrations, executive briefings, and stakeholder-ready narratives.
- Translate complex data architecture, data engineering, analytics, and AI concepts into clear business requirements, product strategies, and implementation priorities.
- Build consensus across stakeholders when data definitions, product priorities, implementation approaches, or delivery timelines differ.
- Provide clear guidance to others.
- Mentor analysts and other delivery professionals on data product management, data analysis, data quality, governance, and stakeholder engagement.
- Communicate regularly with Engagement Managers, project team members, and representatives from various functional and/or technical teams, including escalating any matters that require additional attention and consideration from engagement management.
- Independently and collaboratively lead client engagement workstreams focused on improving analytics capabilities, resolving delivery bottlenecks, and driving operational outcomes.
- Meticulous attention to detail and quality of work product.
- Ability to build and sustain professional relationships.
- Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment.
- Strong interpersonal skills and professional demeanor.
- Ability to meet deadlines.
The Team
AI & Data - AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated solutions across software, data, AI, networks, and cloud infrastructure. These solutions are powered by engineering for business advantage, helping transform mission-critical operations. Our teams enable clients to modernize technology and data platforms while delivering scalable, high-value outcomes tailored to their business needs.
Qualifications
Required
- Bachelor's degree in computer science, Engineering, Data Science, Information Systems, Analytics, or a related field, or equivalent practical experience.
- 6+ years of experience across data product management, data product analysis, data engineering, analytics engineering, BI/reporting, data science, data governance, or related technical roles.
- 3+ years of experience supporting data product, AI/ML, generative AI, advanced analytics, or data-driven transformation initiatives.
- 6+ years of experience working with data products, data analysis, data engineering, analytics, or related data and technology capabilities.
- Advanced proficiency in SQL, including complex joins, common table expressions, window functions, data profiling, data validation, and analytical query development.
- Experience with data engineering patterns and at least 1 processing, transformation, or orchestration technology such as Spark, Airflow, dbt, or equivalent.
- Demonstrated experience building, managing, or delivering enterprise data products, semantic layers, metrics layers, data models, governed APIs, or reusable structured data services.
- Working knowledge of data governance, metadata management, data cataloging, data lineage, data quality, access control, privacy, security, and compliance practices.
- Experience gathering, analyzing, and documenting business, technical, and data product requirements.
- Experience defining product success metrics, user adoption KPIs, acceptance criteria, operational indicators, and measurable business outcomes.
- Experience evaluating data usability, quality, discoverability, accessibility, timeliness, and business value.
- Limited immigration sponsorship may be available.
- Ability to travel up to 10%, on average, based on project and client needs.
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 $107,900.00 to $179,900.00.
Preferred
- Experience using Python for data analysis, automation, data validation, data quality, or data engineering use cases.
- Experience with BI and reporting platforms, enterprise dashboards, governed metrics, or self-service analytics.
- Working knowledge of knowledge graphs, graph-based data models, entity resolution, or relationship-oriented data products.
- Experience with cloud data platforms and modern data ecosystems, such as Snowflake, Databricks, Microsoft Azure, AWS, or Google Cloud.
- Experience with data catalog, governance, metadata, or data quality platforms such as Collibra, Alation, Informatica, Microsoft Purview, or equivalent tools.
- Experience supporting AI/ML or generative AI solutions through trusted datasets, governed data products, reusable features, or responsible data practices.
- Experience working in cross-functional product, analytics, engineering, and QA environments.
- Experience conducting product experiments, user research, stakeholder interviews, or market research.
- Experience maintaining data product roadmaps, release plans, product backlogs, and operational support models.
- Agile delivery experience, including backlog management, sprint planning, release planning, and dependency tracking.
- Experience working in a staff augmentation, delivery center, shared services, or product-aligned operating model.
- Ability to manage multiple priorities and stakeholders with minimal supervision.
Benefits
At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Deloitte can mean for you.
Recruiting tips
From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters.
Our people and culture
Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work.
Our purpose
Deloitte's purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Learn more.
Professional development
From entry-level employees to senior leaders, we believe there's always room to learn. We offer opportunities to build new skills, take on leadership opportunities and connect and grow through mentorship. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career.
Qualified applicants with criminal histories, including arrest or conviction records, will be considered for employment in accordance with the requirements of applicable state and local laws, including the Los Angeles County Fair Chance Ordinance for Employers, City of Los Angeles's Fair Chance Initiative for Hiring Ordinance, San Francisco Fair Chance Ordinance, and the California Fair Chance Act. See notices of various fair chance hiring and ban-the-box laws where available. Fair Chance Hiring and Ban-the-Box Notices - Deloitte US Careers
See all HR Analyst Jobs at Deloitte
Sign up for free to unlock all listings, filter by visa type, and get alerts for new HR Analyst Jobs at Deloitte.
Get Access To All JobsTips for Finding HR Analyst Jobs at Deloitte
Frame your degree around specialty occupation
HR Analyst roles at Deloitte typically require a degree in Human Resources, Industrial-Organizational Psychology, or Business Analytics. Make sure your credentials clearly map to those fields before applying, because USCIS evaluates whether your degree directly relates to the role.
Target Deloitte's consulting-aligned HR openings
Deloitte posts HR Analyst roles across its advisory, consulting, and internal talent functions. Roles tied to workforce transformation or people analytics tend to have a stronger specialty occupation profile than general HR coordinator positions, which matters during visa filing.
Understand which visa fits your situation
Deloitte sponsors H-1B, H-1B1 visa, and E-3 visas for HR Analysts. If you're Australian, the E-3 is faster and avoids the H-1B lottery entirely. If you're on OPT or STEM OPT, confirm your cap-gap timeline before accepting an offer with a delayed start date.
Ask about LCA filing early in negotiations
Deloitte's immigration team files a Labor Condition Application with the DOL before submitting your H-1B petition. Confirm your work location and job title are finalized before that filing, because changes after LCA certification can require amendments and delay your start date.
Browse verified sponsorship-ready HR Analyst roles
Use Migrate Mate to filter HR Analyst openings at Deloitte that are flagged for visa sponsorship. This saves time you'd otherwise spend applying to roles where sponsorship isn't available before you reach the offer stage.
Prepare for Deloitte's structured interview process
Deloitte's HR Analyst interviews often include behavioral rounds and a case or data exercise tied to workforce metrics. Arriving with examples of HR analytics projects, HRIS platform experience, or people strategy work gives you a concrete edge over candidates with only generalist HR backgrounds.
Frequently Asked Questions
Does Deloitte sponsor H-1B visas for HR Analysts?
Yes, Deloitte sponsors H-1B visas for HR Analyst roles. Because the H-1B is subject to an annual lottery, your petition must be selected before Deloitte can proceed with filing. If you're on OPT, timing your offer around the April lottery window is critical to avoid gaps in work authorization.
Which visa types does Deloitte commonly use for HR Analyst roles?
Deloitte sponsors H-1B, H-1B1 visa, and E-3 visas for HR Analysts, along with immigrant visa pathways including EB-2 and EB-3 for longer-term permanent residency. Australian citizens can use the E-3 visa to skip the H-1B lottery entirely. The right visa depends on your nationality, current status, and how quickly you need to start.
How do I apply for HR Analyst jobs at Deloitte?
Applications go through Deloitte's careers portal, where HR Analyst roles are posted by service line and location. You can also browse open positions filtered specifically for visa sponsorship on Migrate Mate, which helps you identify roles where sponsorship is confirmed before you invest time in the application process.
What qualifications does Deloitte expect for HR Analyst roles?
Most HR Analyst roles at Deloitte require a bachelor's degree in Human Resources, Business, Industrial-Organizational Psychology, or a closely related field. Experience with HRIS platforms, workforce data analysis, or HR operations is commonly expected. Consulting-aligned roles may also look for exposure to talent strategy or organizational effectiveness work.
How do I plan my timeline if Deloitte is sponsoring my H-1B?
USCIS accepts H-1B petitions starting April 1 each year, with an employment start date no earlier than October 1. If you're on OPT, your authorization needs to cover the gap between your offer and October. If Deloitte uses premium processing, you'll typically get a decision within 15 business days of filing.