Data Product Manager (Lead)

Data Product Manager (Lead)

Quick Facts

• Lead data product roadmap covering feature stores, decisioning/underwriting datasets, and self-service analytics.
• AI-first approach with AI agents, guardrails, evaluation, and human oversight.
• Track product performance metrics (adoption, self-service usage, decisioning-data SLAs) and coordinate up to 3 data consultants.
• Hybrid working model with preference for 1 day/week in Warsaw or Krakow.

Description

Lead the planning, prioritization, and delivery of data products, ensuring alignment with business value, commercial objectives, and risk impact. You will translate credit, underwriting, fraud prevention, and business requirements into clear product specifications and acceptance criteria for Data Engineering and ML/MLOps teams. You will drive an AI-first approach by integrating AI agents into decision-making with appropriate guardrails, evaluation mechanisms, and human oversight.

Responsibilities

• Define, manage, and prioritize data product roadmaps (feature stores, decisioning/underwriting datasets, self-service analytics).
• Align product priorities and investments with business value, commercial objectives, and risk impact.
• Convert credit, underwriting, fraud prevention, and business requirements into actionable specs for Data Engineering and ML teams.
• Collaborate with Data Engineering and ML/MLOps leadership to align roadmaps with platform architecture, technical capacity, and delivery schedules.
• Drive AI-first data product development with AI agents, guardrails, evaluation mechanisms, and human oversight.
• Lead and coordinate up to 3 Data Consultants, including capacity planning across BNPL and Payments domains.
• Establish and monitor product performance metrics: adoption, self-service analytics usage, and decisioning-data SLAs.
• Communicate roadmap progress, priorities, risks, and trade-offs to senior management and cross-functional stakeholders.
• Support data product development using Databricks lakehouse architecture, feature stores, alternative data sources, and payment partner integrations.
• Promote LLM-assisted analytics and agentic tools to improve team efficiency and data product delivery.

Requirements

• Minimum 5 years of experience in Data Product Management or managing data platforms and analytics products.
• At least 3 years of FinTech experience in credit, lending, or payments, including BNPL, underwriting, or acquiring processes.
• Proven experience defining and managing data product roadmaps for feature stores, decisioning datasets, and self-service analytics.
• Hands-on SQL skills and strong understanding of data quality, freshness, lineage, and point-in-time correctness.
• Ability to translate business, credit risk, and ML requirements into clear, actionable technical specifications.
• Minimum 2 years of experience in AI-first data product initiatives (AI agents, guardrails, evaluations, human-in-the-loop).
• Experience leading or coordinating technical and analytical teams, including resource and capacity planning.
• Understanding of regulatory requirements related to credit, payments, and data management.
• Experience collaborating with Data Engineering, ML, and business stakeholders across multiple product areas.
• Very good English and Polish.

Benefits

• Private medical care
• Sports card
• Training courses
• International working environment and international projects
• Small team
• Hybrid working model: preferably 1 day per week in Warsaw or Krakow office