AI-Driven Product Manager, Client Data Onboarding

Mastercard; Dublin; On-site; EUR 90,000 - 130,000; Full time

Job summary

Mastercard in Dublin is seeking an experienced Specialist, Product Management to drive AI-led client data onboarding within the BE&O team. You will translate user needs into actionable requirements and partner with Engineering, Data Science and UX to ship scalable data onboarding features.

You will own backlog prioritization, define success metrics, assess risks, and ensure governance on data privacy, security and responsible AI while collaborating across R&C and FI pillars to support

Qualifications

• Experience in product management for data/analytics platforms.
• Knowledge of AI, LLMs, and agent-based workflows.
• Understanding of data pipelines, ETL, and data quality.
• Ability to translate user problems into clear requirements and acceptance criteria.
• Strong communication and stakeholder coordination.

Responsibilities

• Support features of our AI-led data onboarding product, focusing on data pipelines and onboarding UX.
• Collaborate with Engineering and Data Science to document requirements and write specs.
• Gather feedback from Data Engineers and ACS users and test agent outputs.
• Define outcomes, success metrics, and risks; manage backlog and prioritization.
• Coordinate with data ingestion, Databricks setup, and data migration; monitor dependencies.
• Ensure governance on security, PCI/PII handling and responsible AI.

Skills

Product management

AI & LLMs

Data pipelines

Privacy awareness

Stakeholder coordination

Communication skills

Independent work

User feedback analysis

Regulated environment

Tools

Databricks

Job description

Mastercard in Dublin is seeking an experienced Specialist, Product Management to drive AI-led client data onboarding within the BE&O team. You will translate user needs into actionable requirements and partner with Engineering, Data Science and UX to ship scalable data onboarding features.

You will own backlog prioritization, define success metrics, assess risks, and ensure governance on data privacy, security and responsible AI while collaborating across R&C and FI pillars to support