Director, Data Products & Management (Fintech Engineering)

Quick Facts

• Role: Data & AI leadership for a new fintech data-first build

Description

You will join the core leadership team to build an AI-first European fintech engine from a blank page, turning real payments/checkout/delivery data into business value. Own the Data & AI strategy and delivery, including an agent-first production approach, a governed Databricks lakehouse ML and MLOps stack, and a unified data/ML foundation with feature store and decisioning. Ensure real-time, explainable, auditable credit and risk decisions with strong governance for GDPR, CCD2, and DORA.

Responsibilities

• Own Data & AI strategy for the fintech build and drive execution
• Build from scratch the Data Engineering & Analytics, ML & MLOps, and Data Product organization (structure, standards, hiring)
• Manage budget, including platform/tooling spend (e.g., Databricks/lakehouse), and defend trade-offs to leadership
• Provide board-level reporting on platform readiness, governance, and delivery risks
• Set architecture and modeling patterns with staff and leadership
• Define and run the agentic standard for ML: agent iteration, monitoring, observability; own reliability, cost, and latency of agent loops/graphs in production
• Own the ML platform (serving, monitoring, retraining), feature store, agent evaluation/observability layer, and partner with Data Engineering and Credit Risk teams

Requirements

• 8+ years leading data engineering or ML organizations
• 5+ years managing managers or team leads
• Financial services, payments, or lending data platform experience (lakehouse, feature store, point-in-time-correct serving)
• Production architect of agentic systems (agentic harnesses and loop/graph workflows) with 3+ years hands-on experience
• Agentic approaches across the ML lifecycle (feature stores, iteration, monitoring/observability)
• Treat agents as first-class production components (orchestration, guardrails, evals, human-in-the-loop, observability, cost/latency)
• Built and led ML teams in regulated settings
• Fluent in Databricks/Spark at scale
• Comfortable partnering with VP/C-level stakeholders
• English fluency (B2+)

Benefits

• Seat at the table with executive backing and extreme ownership
• First hire with a clear mandate and ability to build the organization
• Access to real data at scale (17 million app users) to drive valuable decisions
• Lean, AI-native organization with fast decision cycles