Principal Data Engineer Location Geneva,… at Cargill · Location…

Job Purpose and Impact

• The Advisor, Data Engineering will own the Trading and Risk Management (TRM) data strategy and drive its execution: translating trading ambitions into a prioritized roadmap of trusted, governed and reusable data products, and defining the information architecture required for AI-enabled trading.

  This is a hands-on leadership role for someone equally credible shaping strategy with executives and challenging a pipeline design with engineers. You will partner with data teams across the organization to drive execution and convert fragmented demand into measurable business outcomes.

Key Accountabilities

• DATA STRATEGY & ROADMAP: Defines the TRM data strategy, target state, priorities and value cases. Translates trading and risk-management ambitions into a sequenced roadmap, investment choices, measurable outcomes and an execution backlog, partnering with the product teams across the organization. Leads directly or partners with other data teams to evolve critical datasets into governed, high-quality, reusable data products fit for analytics, AI and trading needs. Works across the organization to define clear ownership, stewardship, quality standards and lifecycle management.
• INFORMATION ARCHITECTURE: Shape, balancing corporate standards and specific trading and risk management needs, and steward the TRM information architecture, including data products, domain and semantic models, metadata, lineage and AI-ready foundations. Ensures architecture decisions support discoverability, reuse, interoperability and trusted decision-making. Partners with data functions, data architecture, security and governance teams to adopt common standards and operating models across data capture, storage, transformation and access while defining well-governed exceptions when required to meet distinctive TRM needs.
• DEEP TECHNICAL LEADERSHIP: Serves as the technical authority for TRM data engineering. Reviews and challenges platform, pipeline, modeling and integration designs; guides engineers through complex trade-offs; and ensures solutions are scalable, observable, resilient, secure, maintainable and ready for advanced analytics and AI workloads for TRM. Provides leadership and guidance to product teams to address high-value needs and successfully executes the TRM data strategy. Converts fragmented or ad hoc requests into a transparent, prioritized backlog with clear delivery metrics and business outcomes.
• TRADING DOMAIN PARTNERSHIP: Builds trusted relationships with trading, risk, operations and technology leaders to understand decision workflows, identify data constraints and shape pragmatic solutions. Communicates complex data and architecture choices clearly to executive and technical audiences.
• CAPABILITY BUILDING: Develops and coaches high-performing data resources across teams. Clarifies roles and ways of working across data strategy, architecture, engineering, product ownership and stewardship, while strengthening data-product and AI-readiness capabilities across TRM.

Qualifications

• Minimum requirement of 8 years of relevant work experience.
• Preferred candidates will typically bring 10+ years of progressive experience spanning data strategy, information architecture, data products, governance and execution, including leadership in a complex trading, commodities, financial-markets or risk-management environment.

Role-Specific Capabilities & Experience

• DEEP DATA ENGINEERING & PLATFORM EXPERTISE: Deep, hands-on engineering credibility on a modern cloud data stack in complex, mission-critical environments, combined with the architectural judgement to choose the right platform pattern and make governed data consumable by analytics and AI. Proven depth across data pipelines, distributed processing, data modeling, lineage, data quality, orchestration and production. Strong command of cloud-native and event-driven architectures, batch and streaming patterns, APIs and data contracts, and the judgement to make deliberate platform and cost trade-offs. Familiarity with agent-oriented data access patterns and with the tension between broad, cross-domain access and least-privilege controls is a strong advantage.
• TRADING & RISK DOMAIN EXPERIENCE: Demonstrated understanding of front-to-back trading and risk-management processes, decision workflows and data needs. Experience in commodities or another asset-intensive trading environment is strongly preferred.
• STRATEGIC DATA LEADERSHIP: Proven ability to translate business strategy into data capabilities, target-state architecture, roadmaps, investment priorities and measurable value.
• COMMUNICATION AND PARTNERSHIP: Clear, influential leader who brings clarity to ambiguity, challenges constructively and inspires action across organizational boundaries. Delivers results by mobilizing capabilities across multiple teams and using strong influencing and negotiation skills with business, engineering, architecture and governance stakeholders. Balances speed to market with enterprise standards and sustainable design.
• EDUCATION: Bachelor's degree in computer science, engineering, information systems, data management or a related field, or equivalent practical experience. An advanced degree is valued but not required.