Data Architect

Company Description

Fastmarkets is an industry‑leading price‑reporting agency (PRA) and information provider for global commodities, offering price data, news, analytics and events across agriculture, forest products, metals and mining, and new‑generation energy markets. With more than 700 employees worldwide, Fastmarkets has a heritage dating back to 1865 and operates in the UK, US, China, India, Singapore, Brazil, Belgium, Bulgaria and Finland.

The Fastmarkets Data team is a new and dynamic function supporting the business in developing and delivering our data strategy through data insights and business intelligence. Working across decentralized teams, the Data Architect will shape and guide our data architecture strategy, translating business requirements into detailed technical specifications, defining data quality frameworks and establishing robust data modelling standards. The role will act as a technical authority, analysing and challenging design patterns introduced by federated teams to ensure consistency, best practices and architectural alignment.

The successful candidate will leverage AI tools throughout their workflow and identify opportunities for AI‑driven innovation across the data platform.

• Collaborate with Business Analysts to manage and refine the product backlog
• Translate high‑level business requirements into detailed technical specifications and user stories
• Define technical requirements for data products, pipelines, and platform capabilities
• Provide technical input on story estimation, complexity, and dependencies
• Document architectural decisions and create comprehensive technical documentation
• Work with Senior Data Engineers and MI/Operational reporting teams to refine technical implementation approaches
• Bridge the gap between business requirements and technical implementation

• Design and maintain the overall data architecture strategy for the Snowflake‑based modern data platform
• Define and implement data modelling standards, patterns, and best practices
• Create conceptual, logical, and physical data models that support business requirements
• Establish and maintain data modelling frameworks (including Data Vault methodology where appropriate)
• Ensure data models are optimised for performance, scalability and maintainability
• Design integration patterns for ingesting data from diverse sources

• Define comprehensive data quality check definitions and validation rules
• Establish data quality standards and metrics across the platform
• Design data quality monitoring and alerting frameworks
• Work with Data Governance Manager to ensure data quality aligns with governance policies
• Implement data quality best practices throughout the data lifecycle

• Analyse and critically evaluate design patterns introduced by decentralised/federated teams
• Challenge proposed solutions to ensure architectural consistency and adherence to best practices
• Provide technical guidance and recommendations to distributed teams
• Balance team autonomy with centralised architectural standards
• Conduct architecture reviews and design critiques
• Identify and resolve architectural conflicts or inconsistencies across teams

• Leverage AI tools (e.g., ChatGPT, Claude, Git Hub Copilot) throughout daily workflows for documentation, code generation and problem‑solving
• Identify opportunities to integrate AI capabilities into data architecture and workflows
• Evaluate and recommend AI‑driven solutions for data quality, metadata management and automation
• Stay current with AI developments relevant to data architecture and analytics

• Define and enforce best practices for Snowflake, DBT, Dagster and the broader modern data stack
• Optimise data platform performance through effective architecture and design
• Establish standards for code quality, testing and deployment
• Ensure alignment with Data Ops principles and "data‑as‑code" approach
• Continuously evaluate new technologies and tools for potential adoption

• Data Platform & AI Manager
• Bus…