Workforce Data Tech Product Manager (Hybrid, AI‑Driven)

MetLife

Cary (NC)

Hybrid

USD 144,000 - 213,000

Full time

2 days ago

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Benefits offered by this job

Health plan

Life insurance

401(k) with match

Disability insurance

Parental leave

Tuition assistance

Paid time off

Paid holidays

Volunteer time off

Job summary

MetLife is seeking a Technology Product Manager for Workforce Data to shape the strategy, roadmap, and outcomes for enterprise data capabilities. You will influence across HR, Technology, Data, and Risk to deliver scalable data products and AI-enabled solutions.

Hybrid role with in-office collaboration required; salary range is $144,100–$213,100 with incentives. You will align stakeholders, ensure data governance, and drive adoption while maintaining ethical AI practices and regulatory

Qualifications

7+ years in technology product management or data products.
Proven ownership of product strategy and roadmaps for enterprise tech/data capabilities.
Strong data product concepts including metadata, lineage, APIs, analytics consumption.
Experience translating workforce/HR needs into product outcomes.
Ability to balance value, risk, cost, time, quality in decisions.
Experience partnering with data engineering, security, privacy, risk, and business teams.
Executive communication and stakeholder alignment at senior levels.
Knowledge of Agile and product operating practices.
Bachelor’s degree in tech/data/analytics/business/HR or equivalent.

Responsibilities

Own workforce data product vision and multi-horizon roadmap.
Lead discovery with stakeholders to identify high-value problems and use cases.
Define portfolio spanning data domains, AI-ready patterns, and reporting enablement.
Create prioritization frameworks balancing value, risk, architecture, and cost.
Collaborate with architecture, data engineering, security, privacy, and platform teams.
Maintain backlog and release-ready increments with clear value.
Communicate decisions to senior audiences in concise language.
Define health metrics: adoption, data quality, timeliness, reliability.
Champion governance, privacy-by-design, and responsible AI considerations.
Guide change, adoption, and lifecycle management across teams.
Serve as trusted product thought-partner across the organization.