Product Management Specialist (Client Data Onboarding, BE&O)

Mastercard; Ireland; Sur place; EUR 85 000 - 110 000; Plein temps

Résumé du poste

Mastercard is seeking an AI-native Specialist, Product Management to help deliver and enhance our AI-led client data onboarding product. You will translate user problems into clear requirements, collaborate with Engineering and Data Science, and shape how we onboard clients across industries.

You will define outcomes, track performance, maintain the backlog, and ensure security and responsible AI practices.

Qualifications

• Ability to gather and interpret user feedback, usage data and operational measures to support product decisions.
• Relevant experience in product management or a related discipline, preferably supporting data, analytics, data engineering or platform products.
• Awareness of data privacy, security and responsible AI considerations, ideally in a regulated or financial-services environment.
• Practical understanding of product management processes and tools, including user discovery, requirements, backlogs, agile delivery, launch readiness and performance tracking.
• A clear communicator who documents requirements, explains progress and raises risks or unclear decisions promptly.
• Experience translating user or business problems into clear requirements, acceptance criteria and measurable success indicators.
• Experience coordinating delivery or readiness activities across technology and business stakeholders, and tracking dependencies through to resolution.
• Interest in, or experience of, building with AI, LLMs and agents, including human-in-the-loop workflows.
• Awareness of data pipelines, ETL, data modelling, data contracts, semantic layers, data quality and platforms such as Databricks; hands-on data engineering is not required.
• Comfortable managing defined work independently while seeking guidance on complex, ambiguous or high-impact decisions.

Responsabilités

• Support assigned features of our AI-led client data onboarding product, with focus on data pipelines, data quality and onboarding UX.
• Write feature specifications, acceptance criteria and functional/non-functional requirements for agents, automated data loading, data quality checks and the web app.
• Collaborate with Engineering and Data Science leads to document requirements and keep users in control by gathering feedback from Data Engineers and ACS users.
• Define outcomes, success measures and risks for assigned features, maintain portions of the product backlog, and support roadmap alignment.
• Coordinate with owners of client connectivity, data ingestion, Databricks setup, data migration, and resolve material concerns as needed.

Connaissances

Product management

Data pipelines

Data quality

AI/LLMs

Agile delivery

Requirements writing

Stakeholder coordination

Privacy & security

Communication

Human-in-the-loop

Outils

Databricks

Description du poste

• As a member of the Client Data Onboarding Product Management team, you will help deliver and improve our AI-led client data onboarding product. We are rapidly replacing manual ETL with agentic workflows, evolving how we onboard clients in the age of AI, and scaling onboarding across industries and pillars
• We are looking for an AI-native Specialist, Product Management who applies practical product management knowledge and established team practices to support assigned features, from user problem through requirements, delivery readiness and performance tracking
• This role reports to the Product Manager within BEO's Client Data Onboarding team
• Support assigned features of our AI-led client data onboarding product, with specific focus on data pipelines, data quality and the onboarding user experience, within established product strategies and roadmaps
• Work with Engineering and Data Science leads to document requirements for the agentic data onboarding workflows. Write feature specifications, acceptance criteria and functional and non-functional requirements for agents, automated data loading, data quality checks and the web app
• Help keep users in control. Work with UX to gather feedback from Data Engineers and ACS users, and test how well they can review, edit and approve agent outputs and answer Client Data Requests (CDRs)
• Validate user problems and proposed solutions using user feedback, usage data, client data insights and structured testing. Define intended outcomes, success measures and key risks for assigned features
• Maintain defined portions of the product backlog and support prioritization by gathering evidence on user value, business impact, delivery effort and risk, in line with the roadmap from the early adopter MVP to scale across R&C industries and FI clients
• Support end-to-end delivery of assigned features. Support development and end-to-end testing, track onboarding time, approval effort, data quality and reduction in manual Data Delivery support, and recommend corrective actions or backlog adjustments
• Track dependencies and delivery risks. Coordinate with the owners of client connectivity, the data ingestion pipeline, Databricks set-up, historical data migration from APT and Data Engineer capacity. Resolve defined issues and elevate material concerns when required
• Support governance and launch readiness. Collect evidence for responsible AI, security, privacy, data, architecture and BizOps reviews, including the correct handling of PCI/PII data
• Maintain accurate product documentation, including feature specifications, decision logs, user guidance and release notes
• Work as a part of a cross-functional product team to bring ideas to life. Coordinate with Engineering, UX, Data Delivery, ACS, the R&C and FI pillars, and C&D to support client roll-out plans
• Abide by Mastercard's security policies and practices
• Ensure the confidentiality and integrity of the information being accessed
• Report any suspected information security violation or breach
• Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines

Ability to gather and interpret user feedback, usage data and operational measures to support product decisionsRelevant experience in product management or a related discipline, preferably supporting data, analytics, data engineering or platform productsAwareness of data privacy, security and responsible AI considerations, ideally in a regulated or financial-services environmentPractical understanding of product management processes and tools, including user discovery, requirements, backlogs, agile delivery, launch readiness and performance trackingA clear communicator who documents requirements, explains progress and raises risks or unclear decisions promptlyExperience translating user or business problems into clear requirements, acceptance criteria and measurable success indicatorsExperience coordinating delivery or readiness activities across technology and business stakeholders, and tracking dependencies through to resolutionInterest in, or experience of, building with AI, LLMs and agents, including human-in-the-loop workflowsAwareness of data pipelines, ETL, data modelling, data contracts, semantic layers, data quality and platforms such as Databricks; hands-on data engineering is not requiredComfortable managing defined work independently while seeking guidance on complex, ambiguous or high-impact decisions