Data Product Lead - Fintech Engineering (m/f/n)

The mission Own the data products that every credit and payments decision at InPost FinTech depends on, across both BNPL and Acquiring & Payments. • Roadmap with impact. You own and prioritise the roadmap for feature stores, decisioning and underwriting datasets and self-serve analytics products. You sequence investment against commercial and risk impact. • Requirements that can be built. You translate credit, underwriting, fraud and commercial needs into clear, prioritised data-product specs and acceptance criteria that Data Engineering and ML teams can build against. • Aligned with the platform. You partner with the Head of Data Engineering & Analytics and the Head of ML & MLOps Engineering. Together you align the roadmap with platform capacity, feature-store architecture and delivery sequencing. • Agent-first by default. You set AI-first / agentic delivery as the team’s default. You shape data products where agents are first-class components of the decisioning surface, with guardrails, evals and human-in-the-loop. You lead the Data Consultants to work AI-first. • Outcomes, not feature lists. You define and track success metrics for the portfolio (adoption, self-serve usage, decisioning-data SLAs). You report progress and trade-offs to the Data Products & Management Director and cross-functional stakeholders. • A team that flexes with demand. You lead up to 3 Data Consultants, who flex against demand across both domains. You are responsible for their capacity planning. What you will work with The feature store, decisioning and underwriting datasets, a Databricks lakehouse platform, self-serve analytics products, and LLM-assisted and agentic tooling. You will also work with data from alternative-data providers and payment-scheme/acquirer partners. You are: • Someone who loves data and loves turning it into products that move money-making decisions. • Hands-on first. You interrogate data yourself with SQL and use AI as a daily tool. • Experienced, with 5+ years in product management for data products or data platforms, including leading or coordinating technical and analytical teams (direct or matrixed). • Experienced in fintech, credit, lending or payments (3+ years) , with knowledge of BNPL origination, underwriting and transaction/acquiring flows. • Strong in data-product strategy and roadmap ownership for feature stores and decisioning datasets. You are fluent in point-in-time correctness, freshness, lineage and self-serve enablement. • Skilled at converting business, credit-risk and ML needs into buildable, prioritised specs. You manage stakeholders and roadmaps across multiple product lines and delivery teams. • Aware of the regulation that governs credit and payments data. • Experienced in AI-first data-product leadership (2+ years): agents as part of the decisioning/data-product surface, with guardrails, evals, human-in-the-loop and control of agent-loop cost and latency. • A leader who sets AI-first ways of working as the team’s default, including LLM-assisted analysis and agentic tooling, and holds the team to designing with agents, not around them. • Strategic and outcome-focused. You frame data-product decisions as ROI. • Confident translating between Data Engineering / ML and business and risk stakeholders, and influencing without direct authority across Credit & Fraud Risk, Engineering and Commercial teams. • Comfortable prioritising and re-prioritising a roadmap across two product lines under real capacity constraints. • Fluent in English (B2+). Bonus points for: • Feature store or ML-enabled decisioning products • Acquiring / merchant payments data, including merchant acquiring and payment-scheme data structures • ML/MLOps fundamentals, enough to partner credibly with ML & MLOps Engineering