Fintech Data Architect & Modeller for Scalable Architecture

Sanderson; Greater London; In loco; GBP 129.000 - 138.000; Part-time

Descrizione del lavoro

Sanderson is seeking a Lead Data Architect / Modeller for a London-based fintech project. The role focuses on owning long-term data architecture and modelling between engineering delivery and analytics teams, ensuring a scalable, consistent data structure from the outset.

Responsibilities include defining conceptual data models, shaping operational data architecture, and establishing a semantic layer while engaging stakeholders to translate business needs into robust data models.

Competenze

• Strong data architecture and modelling background.
• Fintech sector experience is highly desirable.
• Excellent conceptual and logical data modelling experience.
• Design data structures to support operational workflows and case management.
• Translate business requirements into scalable data models.
• Experience with modern event-driven architectures.
• Ability to challenge stakeholders and align business and engineering teams.
• Able to operate at business and technical architecture levels.

Mansioni

• Define business-led conceptual data model across operational processes.
• Shape the operational data architecture for scale.
• Ensure enterprise data models are scalable, consistent and reusable.
• Help define the semantic layer for analytics.
• Collaborate with stakeholders to understand process operation and requirements.
• Challenge requirements where appropriate and review direction.
• Identify architectural or modelling issues and address them.

Conoscenze

Data Architecture

Data Modelling

Fintech

Conceptual Modelling

Event-driven architecture

Stakeholder engagement

Technical architecture

Operational workflows

Business requirements translation

Strumenti

Snowflake

Descrizione del lavoro

Sanderson is seeking a Lead Data Architect / Modeller for a London-based fintech project. The role focuses on owning long-term data architecture and modelling between engineering delivery and analytics teams, ensuring a scalable, consistent data structure from the outset.

Responsibilities include defining conceptual data models, shaping operational data architecture, and establishing a semantic layer while engaging stakeholders to translate business needs into robust data models.