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.