Data Product Manager Jobs at Deloitte with Visa Sponsorship
Deloitte hires Data Product Managers across its consulting and technology practices, sponsoring a range of work visas for qualified candidates. If you're targeting this role, Deloitte has a well-established sponsorship process and works with immigration counsel to support H-1B, E-3, and other visa categories.
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Get Access To All JobsINTRODUCTION
Zora AI is Deloitte's AI agent platform delivering role-/function-specific products (e.g., Finance, Procurement, Supply Chain, Customer, Human Capital). As a Product Manager, you will own one or more sets of agent-enabled products end-to-end-defining vision, roadmap, requirements, and delivery-while ensuring trust, adoption, and measurable business outcomes for enterprise users.
Key Responsibilities:
- Own product strategy and roadmap: Define product vision, target users, value propositions, and multi-quarter roadmap across multiple role-/function-specific products.
- Translate needs into outcomes: Partner with clients/internal teams to identify high-value use cases, map workflows, and define "jobs to be done" and measurable success metrics.
- Lead discovery and delivery: Run discovery (research, prototypes, pilots) and delivery (MVP to scale), managing scope, tradeoffs, and dependencies across engineering, data, and design.
- Define product requirements: Create PRDs, user stories, acceptance criteria, and workflow diagrams for agent behaviors, tool integrations, and user experiences.
- Agent experience & orchestration: Specify agent capabilities (reasoning, task planning, tool use, approvals), human-in-the-loop patterns, and escalation/exception handling.
- Data and integration leadership: Drive requirements for connectors, data access patterns, security/privacy, logging/auditability, and integration with enterprise systems.
- Trustworthy AI & risk management: Partner with risk/compliance to address model governance, safety, monitoring, explainability, bias, and audit requirements.
- Go-to-market and enablement: Collaborate with sales and delivery to package offerings, define pricing/packaging inputs, create demos, and support pursuits and launches.
- Operate the product cadence: Maintain backlog, run sprint planning, track progress, and align stakeholders through clear decision points and communications.
Required Qualifications:
- 7+ years of Product Management experience (enterprise software, SaaS, platforms, or data products), including shipping products from concept to GA.
- 2+ years of recent experience delivering products involving AI/ML (GenAI preferred), including evaluation, monitoring, and iteration loops.
- 2+ years of recent experience supporting product discovery (research, hypothesis testing, experimentation) and product delivery (requirements, backlog, release management).
- 1+ year working with enterprise integration patterns (APIs, eventing, identity/SSO, role-based access control, data pipelines).
- Limited immigration sponsorship may be available.
- Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
Preferred:
- Experience with agentic architectures (tool calling, retrieval-augmented generation, workflow orchestration, multi-agent patterns).
- Familiarity with LLM evaluation (quality metrics, red-teaming, grounding, hallucination mitigation) and observability.
- Domain depth in one or more target functions (e.g., Finance, Procurement, Supply Chain, HR, Customer Operations).
- Consulting, enterprise transformation, or platform product experience (shared services, reusable components, governance).
- Proven ability to manage multiple products with competing priorities and shared platform dependencies.
- Experience launching products with OCI / SAP / ERP / CRM ecosystems and connector marketplaces.
- Excellent stakeholder management and executive communication; able to write crisp narratives, PRDs, and decision memos.
- Track record of partnering with engineering, design, data science, and risk/compliance teams to deliver in regulated or high-stakes environments.
Key Deliverables
- Product strategy and 12-18 month roadmap with measurable outcomes.
- PRDs, epics, user stories, and acceptance criteria for each product/agent capability.
- Use-case catalog and prioritization model (value, feasibility, risk, readiness).
- MVP/pilot plans with success metrics, rollout phases, and scale criteria.
- Trust & governance artifacts: evaluation approach, monitoring plan, audit/logging requirements, and risk controls (in partnership with risk teams).
- Release plans and launch readiness checklists (docs, training, demo scripts, enablement).
- Customer feedback loop: telemetry dashboards, VOC insights, and iteration plan.
How success will be measured (example outcomes)
- Adoption: active users, repeat usage, workflow completion rates, feature utilization by product set.
- Business impact: cycle-time reduction for targeted workflows, cost-to-serve reductions, improved forecast accuracy or exception resolution time (by use case).
- Quality & reliability: task success rate, low rework/rollback rates, latency/uptime targets, incident trends.
- Trust & compliance: audit readiness, policy adherence, reduction in high-severity model risks, successful governance reviews.
- Delivery excellence: roadmap predictability, on-time releases, stakeholder satisfaction, reduced dependency blockers.
- Customer outcomes: pilot-to-scale conversion, referenceable wins, renewal/expansion influence (where applicable).
Working model & stakeholders (edit as needed)
- Working model: Remote + Hybrid (2-3 days onsite) with flexibility based on team and client needs; operates in agile product teams with regular release cadence.
- Core stakeholders:
- Engineering (platform + product squads)
- Data Science / Applied AI (models, evaluation, tuning)
- Design / Research (UX, workflow design, prototyping)
- Cybersecurity & Privacy (security controls, data protection)
- Risk, Legal, Compliance (AI governance, auditability, policy alignment)
- Domain SMEs (Finance, Procurement, Supply Chain, HR, etc.)
- Sales, Alliances, and Delivery/Implementation (pursuits, packaging, rollout)
- Customer/Client stakeholders (product owners, process owners, IT, operations)
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 $102,000 - $210,000.
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
EA_ITS_ExpHire
INTRODUCTION
Zora AI is Deloitte's AI agent platform delivering role-/function-specific products (e.g., Finance, Procurement, Supply Chain, Customer, Human Capital). As a Product Manager, you will own one or more sets of agent-enabled products end-to-end-defining vision, roadmap, requirements, and delivery-while ensuring trust, adoption, and measurable business outcomes for enterprise users.
Key Responsibilities:
- Own product strategy and roadmap: Define product vision, target users, value propositions, and multi-quarter roadmap across multiple role-/function-specific products.
- Translate needs into outcomes: Partner with clients/internal teams to identify high-value use cases, map workflows, and define "jobs to be done" and measurable success metrics.
- Lead discovery and delivery: Run discovery (research, prototypes, pilots) and delivery (MVP to scale), managing scope, tradeoffs, and dependencies across engineering, data, and design.
- Define product requirements: Create PRDs, user stories, acceptance criteria, and workflow diagrams for agent behaviors, tool integrations, and user experiences.
- Agent experience & orchestration: Specify agent capabilities (reasoning, task planning, tool use, approvals), human-in-the-loop patterns, and escalation/exception handling.
- Data and integration leadership: Drive requirements for connectors, data access patterns, security/privacy, logging/auditability, and integration with enterprise systems.
- Trustworthy AI & risk management: Partner with risk/compliance to address model governance, safety, monitoring, explainability, bias, and audit requirements.
- Go-to-market and enablement: Collaborate with sales and delivery to package offerings, define pricing/packaging inputs, create demos, and support pursuits and launches.
- Operate the product cadence: Maintain backlog, run sprint planning, track progress, and align stakeholders through clear decision points and communications.
Required Qualifications:
- 7+ years of Product Management experience (enterprise software, SaaS, platforms, or data products), including shipping products from concept to GA.
- 2+ years of recent experience delivering products involving AI/ML (GenAI preferred), including evaluation, monitoring, and iteration loops.
- 2+ years of recent experience supporting product discovery (research, hypothesis testing, experimentation) and product delivery (requirements, backlog, release management).
- 1+ year working with enterprise integration patterns (APIs, eventing, identity/SSO, role-based access control, data pipelines).
- Limited immigration sponsorship may be available.
- Ability to travel 0-10%, on average, based on the work you do and the clients and industries/sectors you serve.
Preferred:
- Experience with agentic architectures (tool calling, retrieval-augmented generation, workflow orchestration, multi-agent patterns).
- Familiarity with LLM evaluation (quality metrics, red-teaming, grounding, hallucination mitigation) and observability.
- Domain depth in one or more target functions (e.g., Finance, Procurement, Supply Chain, HR, Customer Operations).
- Consulting, enterprise transformation, or platform product experience (shared services, reusable components, governance).
- Proven ability to manage multiple products with competing priorities and shared platform dependencies.
- Experience launching products with OCI / SAP / ERP / CRM ecosystems and connector marketplaces.
- Excellent stakeholder management and executive communication; able to write crisp narratives, PRDs, and decision memos.
- Track record of partnering with engineering, design, data science, and risk/compliance teams to deliver in regulated or high-stakes environments.
Key Deliverables
- Product strategy and 12-18 month roadmap with measurable outcomes.
- PRDs, epics, user stories, and acceptance criteria for each product/agent capability.
- Use-case catalog and prioritization model (value, feasibility, risk, readiness).
- MVP/pilot plans with success metrics, rollout phases, and scale criteria.
- Trust & governance artifacts: evaluation approach, monitoring plan, audit/logging requirements, and risk controls (in partnership with risk teams).
- Release plans and launch readiness checklists (docs, training, demo scripts, enablement).
- Customer feedback loop: telemetry dashboards, VOC insights, and iteration plan.
How success will be measured (example outcomes)
- Adoption: active users, repeat usage, workflow completion rates, feature utilization by product set.
- Business impact: cycle-time reduction for targeted workflows, cost-to-serve reductions, improved forecast accuracy or exception resolution time (by use case).
- Quality & reliability: task success rate, low rework/rollback rates, latency/uptime targets, incident trends.
- Trust & compliance: audit readiness, policy adherence, reduction in high-severity model risks, successful governance reviews.
- Delivery excellence: roadmap predictability, on-time releases, stakeholder satisfaction, reduced dependency blockers.
- Customer outcomes: pilot-to-scale conversion, referenceable wins, renewal/expansion influence (where applicable).
Working model & stakeholders (edit as needed)
- Working model: Remote + Hybrid (2-3 days onsite) with flexibility based on team and client needs; operates in agile product teams with regular release cadence.
- Core stakeholders:
- Engineering (platform + product squads)
- Data Science / Applied AI (models, evaluation, tuning)
- Design / Research (UX, workflow design, prototyping)
- Cybersecurity & Privacy (security controls, data protection)
- Risk, Legal, Compliance (AI governance, auditability, policy alignment)
- Domain SMEs (Finance, Procurement, Supply Chain, HR, etc.)
- Sales, Alliances, and Delivery/Implementation (pursuits, packaging, rollout)
- Customer/Client stakeholders (product owners, process owners, IT, operations)
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 $102,000 - $210,000.
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
EA_ITS_ExpHire
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Get Access To All JobsTips for Finding Data Product Manager Jobs at Deloitte Jobs
Frame your portfolio around client delivery
Deloitte's Data Product Manager roles sit inside client-facing engagements, not internal product teams. Tailor your portfolio to show how you've translated ambiguous client needs into measurable data products, not just internal roadmaps.
Search open roles through Migrate Mate
Use Migrate Mate to filter Data Product Manager openings at Deloitte by visa type. This saves time by surfacing only roles where your specific sponsorship category is supported, so you're not guessing from a generic jobs listing.
Prepare a specialty occupation case for your role
H-1B petitions for Data Product Manager roles require demonstrating specialty occupation status. Document how your position requires a specific bachelor's degree field, such as computer science or information systems, not just any degree.
Align your start date with Deloitte's staffing cycles
Deloitte typically staffs consulting projects on quarterly cycles. If you're negotiating an H-1B transfer or cap-exempt filing, propose a start date that aligns with a project ramp, which reduces internal friction and speeds up offer finalization.
Request PERM timeline clarity before accepting
If green card sponsorship matters to you, ask during the offer stage whether the role qualifies for EB-2 or EB-3 PERM filing. Consulting firms sometimes classify the same title differently across practice areas, which affects your priority date timeline.
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Find Data Product Manager at Deloitte JobsFrequently Asked Questions
Does Deloitte sponsor H-1B visas for Data Product Managers?
Yes, Deloitte sponsors H-1B visas for Data Product Manager roles. The role typically qualifies as a specialty occupation under USCIS standards because it requires a degree in a specific technical or analytical field. If you're transferring from another H-1B employer, Deloitte can file a cap-exempt transfer, so you don't need to wait for the annual lottery.
How do I apply for Data Product Manager jobs at Deloitte?
You can apply directly through Deloitte's careers site or find sponsorship-verified openings on Migrate Mate, which filters roles by visa type. When applying, tailor your resume to highlight client-facing data product work and cross-functional delivery experience. Deloitte's recruiting process for this role typically includes a technical screen, a case-based interview, and a final panel with practice leadership.
Which visa types does Deloitte commonly use for Data Product Managers?
Deloitte sponsors H-1B, H-1B1, E-3, and Green Card pathways including EB-2 and EB-3 for Data Product Manager positions. H-1B is the most common for candidates from India and other countries. Australian citizens can pursue the E-3, which has no lottery and allows faster processing. H-1B1 is available for citizens of Chile and Singapore under specific trade agreements.
What qualifications does Deloitte expect for a sponsored Data Product Manager role?
Deloitte typically expects a bachelor's degree in computer science, information systems, engineering, or a related technical field, plus experience managing data products or analytics platforms in client or enterprise environments. For H-1B purposes, your degree field needs to align directly with the role's responsibilities. Consulting-specific experience, such as working within delivery frameworks or client stakeholder management, strengthens both your application and your visa petition.
How do I time my H-1B filing if I receive an offer from Deloitte?
If you're new to the H-1B and not yet in status, Deloitte would file during the April cap season for an October 1 start date under USCIS's standard timeline. If you're already on an H-1B with another employer, Deloitte can file a transfer petition immediately after your offer, and you can begin work once USCIS issues a receipt notice, typically within a few weeks.
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