Data Architect – Trading & Commodity Data

Role: Data Architect – Trading & Commodity Data

Location: Canary Wharf, UK

Type: Contract (Inside IR35)

Key Responsibilities

Data Architecture & Modeling

• Design and maintain enterprise data architectures supporting trading and position management platforms.
• Develop and govern conceptual, logical, and physical data models across multiple commodities and business domains.
• Analyze existing physical schemas and identify opportunities for optimization, standardization, simplification, and improved performance.
• Design scalable data structures supporting trading, risk, settlements, inventory, analytics, and operational reporting.
• Define and enforce enterprise data standards, naming conventions, modeling principles, and architectural frameworks.
• Ensure data models are scalable, maintainable, and aligned with enterprise architecture principles.

Trading Data Domain Leadership

• Lead architecture discussions covering the trade lifecycle, positions, exposures, inventory, pricing, market data, and related trading data domains.
• Develop cross-commodity data models that promote consistency and reuse across trading businesses.
• Partner with business subject-matter experts to understand complex trading processes and translate requirements into robust data solutions.
• Support integration between trading platforms, operational systems, and downstream analytical environments.
• Identify opportunities to improve the consistency and usability of data across trading and commodity domains.

Data Quality & Governance

• Establish and promote data governance standards covering lineage, metadata, ownership, quality, and lifecycle management.
• Define validation, reconciliation, and data quality frameworks for critical trading and operational data.
• Collaborate with engineering teams to ensure architectural designs are implemented accurately and consistently.
• Review and approve schema changes, data model enhancements, and significant database design decisions.
• Support the identification and resolution of data quality, integrity, and consistency issues.

Technical Leadership

• Act as a primary architecture lead for data-related initiatives.
• Provide architectural guidance to Data Engineers, Platform Engineers, and Application Development teams.
• Review technical designs and implementation deliverables for alignment with approved architecture and data standards.
• Support testing, validation, release, and production deployment activities where required.
• Challenge existing designs and recommend pragmatic improvements based on architectural best practices.

Stakeholder Engagement

• Work closely with traders, analysts, product owners, architects, engineering teams, and other business stakeholders.
• Facilitate architecture workshops, data modeling sessions, and technical design discussions.
• Translate complex business requirements into clear and practical data architecture solutions.
• Communicate solution options, trade-offs, risks, and recommendations effectively to both technical and non-technical audiences.
• Build strong working relationships across business and technology teams.

Required Skills & Experience

Data Architecture & Modeling

• Experience in Data Architecture, Data Modeling, Enterprise Information Architecture, or a related discipline.
• Deep expertise in:
• Conceptual Data Modeling
• Logical Data Modeling
• Physical Data Modeling
• Enterprise Data Architecture
• Data Governance
• Metadata Management
• Data Lineage
• Data Quality

Data Technologies

• Advanced SQL and strong database design expertise.
• Extensive experience with:
• ER/Studio or comparable enterprise data modeling tools
• Entity-Relationship (ER) modeling
• Databricks and modern data platforms
• Relational databases
• Analytical data platforms
• Enterprise data architecture frameworks
• Experience reviewing, validating, and testing engineering implementations against architectural specifications.
• Strong understanding of database performance, scalability, normalization, and physical data design.

Trading & Energy Domain

• Experience working with Trading & Shipping, commodities trading, or comparable financial/physical trading environments .
• Strong understanding of:
• Position Management
• Trade Lifecycle
• Trade Capture
• Market Data
• Risk Data
• Exposure Management
• Inventory Management
• Trading Analytics
• Understanding of physical oil trading processes is highly preferred.
• Experience with ETRM (Energy Trading and Risk Management) platforms is highly desirable.

Additional Preferred Experience

• Experience working with AI-assisted development or architecture tools.
• Experience analyzing and improving large-scale spreadsheet-driven business processes and data structures.
• Knowledge of cloud-based data ecosystems and modern data platforms.
• Familiarity with commodity trading data across multiple commodities.
• Experience with modern lakehouse architectures and enterprise-scale analytical platforms.

Key Attributes

• Strong independent contributor who can operate effectively with minimal supervision.
• Excellent communication, facilitation, and stakeholder management skills.
• Ability to bridge business requirements and technology solutions.
• Strong analytical, problem-solving, and critical-thinking capabilities.
• Comfortable operating within complex, global, and highly integrated trading environments.
• Willingness to challenge existing designs and drive data architecture best practices.
• Pragmatic approach to balancing architectural standards, business needs, delivery timelines, and technical constraints.

Nice to Have

• Physical Oil Trading experience.
• Trading & Shipping domain expertise.
• Experience with ETRM / Position Management platforms.
• Commodity risk management experience.
• Databricks Lakehouse architecture experience.
• Experience with AI-enabled data architecture or development tooling.
• Experience designing enterprise data models spanning multiple commodities and trading domains.