Data Product Lead – 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 within BNPL and Acquiring & Payments.

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

• Sequence investments based on their commercial and risk implications.

• Convert the requirements of credit, underwriting, fraud, and commercial domains into prioritized specifications and acceptance criteria for data products.

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

• Establish an AI-first and agentic delivery approach as the default for the team.

• Design data products that incorporate agents as first-class components, including guardrails, evaluations, and human-in-the-loop controls.

• Guide Data Consultants in adopting AI-first methodologies.

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

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

• Lead a team of up to 3 Data Consultants and oversee their capacity planning.

• Engage with feature stores, decisioning and underwriting datasets, Databricks lakehouse, 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 platforms, with a focus on leading or coordinating technical and analytical teams (either direct or matrixed).

• At least 3 years of experience in fintech, credit, lending, or payments.

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

• Proven track record in data-product strategy and roadmap ownership, particularly for feature stores and decisioning datasets.

• Proficient in concepts such as point-in-time accuracy, data freshness, lineage, and self-service enablement.

• Capability to translate business, credit-risk, and machine learning needs into actionable, prioritized specifications.

• Experience in managing stakeholders and overseeing roadmaps across multiple product lines and delivery teams.

• Knowledge of regulations related to credit and payments data.

• Over 2 years of experience in AI-first data-product leadership, encompassing agents, guardrails, evaluations, human-in-the-loop processes, and managing costs and latency.

• Familiarity with establishing AI-first working methods, including LLM-assisted analysis and agentic tooling.

• A strategic outlook focused on outcomes, with the ability to frame data-product decisions in terms of ROI.

• Proficient in bridging the gap between Data Engineering/ML and business/risk stakeholders, influencing without direct authority.

• Skilled in prioritizing and adjusting roadmaps across two product lines amidst capacity constraints.

• Hands-on experience with SQL and regular use of AI tools.

• Proficient in English (B2+ level).

• B2B contract arrangement.

• Bonus: Experience with feature store or ML-enabled decisioning products, acquiring/merchant payments data, ML/MLOps fundamentals, IFRS 9/credit provisioning data concepts, self-service analytics products, and familiarity with Databricks/lakehouse.

🏝️ Benefits

• Access to a modern technology stack and the opportunity to work within a lean, AI-native team, encouraging experimentation with new technologies and their implementation in production.

• A collaborative and fast-paced environment where autonomy and accountability are key values.