Data Product Owner – Strategy Lead

Role Overview

• Maximizing the value for one or more products.
• Working with stakeholders to understand their needs, and with product managers or specialists to ensure they are aligning on priorities and creating the vision and roadmap for the product to align with strategic direction for the business or technology domain.
• Ensuring delivery of products that meet the expectations of our clients, including features, security, availability, resiliency, timelines and costs.
• Define data domain-level strategies and establishes consistent end-to-end data flow design patterns.
• Coordinate across business and technology teams to synergize efforts across multiple projects.
• Align strategic objectives and enforce standards through governance—reducing rework, ensuring regulatory and audit compliance, and enabling reusable design patterns.
• Drive predictable delivery across a multi-million-dollar portfolio by embedding opportunities for strategic objectives such as data modernization, cloud migration, and AI adoption.

Requirements

• 2+ years of applicable experience with the following skills
• Strong interest in building data-driven products and solutions, with an understanding of how data supports business outcomes in a regulated environment.
• Exposure to banking, payments, treasury, or financial services is advantageous.
• Ability to structure problems, analyse data, and contribute to solution design with a focus on simplification and scalability.
• Strong communication skills with the ability to collaborate across teams and clearly articulate ideas.
• Demonstrated curiosity and willingness to continuously upskill, particularly in areas such as AI, data, and emerging technologies.
• Understanding of payment rails, clearing and settlement, cross-border flows, correspondent banking, or treasury operations; familiarity with ISO 20022 and SWIFT standards.
• Knowledge of regulatory frameworks (e.g. PSD2/Open Banking, AML/Sanctions), data lineage, controls, and audit readiness.
• Experience with canonical data models, APIs, event-driven and batch processing, metadata/lineage, reference/master data, and data quality frameworks.
• Experience in defining standards, control frameworks, and driving adherence to enterprise data and architecture principles.
• Familiarity with enterprise architecture engagement, design patterns, and scaled delivery models (e.g. SAFe, PI Planning).
• Experience defining roadmaps, backlog prioritisation, value articulation, and use case development.
• Exposure to data mesh, product-centric operating models, event streaming (e.g. Kafka), and real-time analytics.
• Experience or strong interest in supporting AI/ML use cases, including data readiness, feature engineering, model lifecycle integration, and explainability.
• Exposure to cloud ecosystems (Azure/AWS), data lake/lakehouse architectures, and modern data platforms.
• Relevant certifications (SAFe, CDMP/DAMA, cloud, data/AI governance) are a plus.

Tech Stack

• AWS
• Azure
• Cloud
• Kafka
• Ruby on Rails
• Swift

Benefits

• affordable, competitive and flexible benefits
• supporting our teammates’ physical, emotional, and financial wellness