Data Product Lead – Fintech Engineering

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🇵🇱 Poland – Remote

⏰ Full Time

🟠 Senior

✅ Product Manager

👻 Ghost score 14%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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InPost Group

WebsiteLinkedInAll Job Openings

10,000+ employees

🛍️ eCommerce

🚗 Transport

📦 Logistics

eCommerce • Transport • Logistics

InPost Group is Europe's leading e-commerce enablement platform, specializing in out-of-home delivery services. Founded in 1999 by CEO Rafal Brzoska, InPost provides cost-effective and environmentally friendly delivery solutions through a robust network of Automated Parcel Machines (APMs) and courier services. The company also offers pick-up drop-off (PUDO) services, enhancing convenience and efficiency for e-commerce merchants across Europe. InPost is committed to sustainability, reducing carbon emissions significantly in its delivery processes. With operations in countries like Poland, France, Benelux, the UK, and Italy, InPost continues to expand its innovative technology solutions to drive long-term growth in the e-commerce sector.

📋 Description

• Own data products supporting credit and payments decisions across BNPL and Acquiring & Payments • Own and prioritise the roadmap for feature stores, decisioning and underwriting datasets, and self-serve analytics products • Sequence investment according to commercial and risk impact • Translate credit, underwriting, fraud and commercial needs into prioritised data-product specifications and acceptance criteria • Partner with the Head of Data Engineering & Analytics and Head of ML & MLOps Engineering to align roadmap, platform capacity, feature-store architecture and delivery sequencing • Set AI-first and agentic delivery as the team default • Shape data products with agents as first-class components, including guardrails, evaluations and human-in-the-loop controls • Lead Data Consultants in AI-first ways of working • Define and track portfolio success metrics, including adoption, self-serve usage and decisioning-data SLAs • Report progress and trade-offs to the Data Products & Management Director and cross-functional stakeholders • Lead up to 3 Data Consultants and manage their capacity planning • Work with feature stores, decisioning and underwriting datasets, Databricks lakehouse, self-serve analytics products, LLM-assisted and agentic tooling, alternative-data providers, and payment-scheme/acquirer partners

🎯 Requirements

• 5+ years in product management for data products or data platforms, including leading or coordinating technical and analytical teams (direct or matrixed) • 3+ years of experience in fintech, credit, lending or payments • Knowledge of BNPL origination, underwriting and transaction/acquiring flows • Strong data-product strategy and roadmap ownership for feature stores and decisioning datasets • Fluency in point-in-time correctness, freshness, lineage and self-serve enablement • Ability to convert business, credit-risk and ML needs into buildable, prioritised specifications • Experience managing stakeholders and roadmaps across multiple product lines and delivery teams • Awareness of regulations governing credit and payments data • 2+ years of experience in AI-first data-product leadership, including agents, guardrails, evaluations, human-in-the-loop, and agent-loop cost and latency control • Experience setting AI-first ways of working, including LLM-assisted analysis and agentic tooling • Strategic and outcome-focused approach; ability to frame data-product decisions as ROI • Ability to translate between Data Engineering/ML and business and risk stakeholders and influence without direct authority • Ability to prioritise and re-prioritise roadmaps across two product lines under capacity constraints • Hands-on SQL skills and daily use of AI tools • Fluent in English (B2+) • B2B contract arrangement • Bonus: feature store or ML-enabled decisioning products; acquiring/merchant payments data; ML/MLOps fundamentals; IFRS 9/credit provisioning data concepts; self-serve analytics products; Databricks/lakehouse familiarity

🏖️ Benefits

• Modern stack and a lean, AI-native team, with space to experiment with new technologies and bring them into production • Collaborative, fast-moving environment where autonomy and accountability go hand in hand