Lead Data Product Manager – Fintech Engineering

This is a fully remote position, open to applicants in Poland.

📋 Description

• Take ownership of data products that facilitate credit and payment decisions across BNPL and Acquiring & Payments.

• Manage and prioritize the roadmap for feature stores, decision-making and underwriting datasets, as well as self-service analytics products.

• Sequence investments based on their commercial and risk implications.

• Convert credit, underwriting, fraud, and commercial requirements into prioritized data-product specifications and acceptance criteria.

• Collaborate with the Head of Data Engineering & Analytics and the Head of ML & MLOps Engineering to ensure alignment on the roadmap, platform capacity, feature-store architecture, and delivery sequencing.

• Establish an AI-first and agentic delivery approach as the team's standard practice.

• Design data products incorporating agents, guardrails, evaluations, and human-in-the-loop controls.

• Lead Data Consultants in adopting AI-first methodologies.

• Define and monitor portfolio success metrics, including adoption rates, self-service usage, and decisioning-data SLAs.

• Communicate progress and trade-offs to the Data Products & Management Director and cross-functional stakeholders.

• Supervise up to three Data Consultants and oversee their capacity planning.

• Work with Databricks lakehouse, feature stores, underwriting datasets, self-service analytics products, LLM-assisted and agentic tools, alternative data providers, and payment scheme/acquirer partners.

⛳️ Requirements

• Over 5 years of experience in product management for data products or data platforms.

• Proven experience in leading or coordinating technical and analytical teams, either directly or through a matrix structure.

• More than 3 years of experience in fintech, credit, lending, or payments.

• Understanding of BNPL origination, underwriting, and transaction/acquiring processes.

• Strong ownership of data-product strategy and roadmap for feature stores and decisioning datasets.

• Proficient in point-in-time correctness, freshness, lineage, and self-service enablement.

• Capability to translate business, credit-risk, and ML requirements into actionable, prioritized specifications.

• Experience in stakeholder and roadmap management across various product lines and delivery teams.

• Knowledge of regulations related to credit and payments data.

• At least 2 years of experience in AI-first data-product leadership, including agents, guardrails, evaluations, human-in-the-loop, and managing agent-loop cost and latency.

• Experience in establishing AI-first working methods, including LLM-assisted analysis and agentic tools.

• Strategic and outcome-oriented mindset, framing data-product decisions in terms of ROI.

• Ability to bridge communication between Data Engineering/ML and business and risk stakeholders.

• Proficiency in influencing stakeholders without direct authority across Credit & Fraud Risk, Engineering, and Commercial teams.

• Skill in prioritizing and adjusting roadmaps across two product lines under capacity limitations.

• Fluent in English (B2+ level).

• Proficient in SQL and hands-on data interrogation.

• Bonus: Experience with feature stores or ML-enabled decisioning products.

• Bonus: Familiarity with acquiring/merchant payments data and payment scheme data structures.

• Bonus: Understanding of ML/MLOps fundamentals.

• Bonus: Knowledge of IFRS 9/credit provisioning data concepts.

• Bonus: Experience with self-service analytics products for commercial or risk teams.

• Bonus: Familiarity with the Databricks/lakehouse platform.

🏝️ Benefits

• Architectural authority from day one.

• Engage in greenfield, high-stakes projects with design decisions that have long-lasting impacts.

• Work with a modern tech stack and be part of a lean, AI-native team.

• Opportunity to experiment with new technologies and implement them in production.

• Collaborative and fast-paced work environment.

• Autonomy and accountability in your role.

• Hybrid work arrangement.

• B2B contract.