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Principal Data Engineer – Trading & Risk Management

Cargill · Genève

Nouveau
Senior 🇬🇧 English
event-driven architectures APIs data contracts data pipelines distributed processing data modeling data quality orchestration

Description du poste

About the role

The Advisor, Data Engineering will own the Trading and Risk Management (TRM) data strategy and drive its execution. This hands‑on leadership role translates trading ambitions into a prioritized roadmap of trusted, governed, reusable data products and defines the information architecture for AI‑enabled trading.

Key responsibilities

  • Define the TRM data strategy, target state, priorities and measurable outcomes, and translate them into a sequenced roadmap and execution backlog.
  • Lead the evolution of critical datasets into governed, high‑quality, reusable data products for analytics, AI and trading.
  • Shape and steward the TRM information architecture, including data products, domain models, metadata, lineage and AI‑ready foundations.
  • Serve as the technical authority for TRM data engineering, reviewing platform, pipeline and modeling designs and ensuring solutions are scalable, observable, resilient and secure.
  • Build trusted relationships with trading, risk, operations and technology leaders to understand workflows and shape pragmatic data solutions.
  • Develop and coach high‑performing data resources, clarifying roles across data strategy, architecture, engineering and product ownership.

Required profile

  • Minimum 8 years of relevant experience; typically 10+ years in data strategy, architecture, governance and execution within a complex trading, commodities or financial‑markets environment.
  • Proven ability to translate business strategy into data capabilities, target‑state architecture, roadmaps and measurable value.
  • Strong communication and partnership skills, able to influence executives and technical audiences.

Required skills

  • Deep hands‑on engineering experience with modern cloud data stacks (cloud‑native, event‑driven architectures, batch and streaming patterns).
  • Expertise in data pipelines, distributed processing, data modeling, lineage, data quality, orchestration and production environments.
  • Proficiency with APIs, data contracts and cost‑aware platform design.
  • Understanding of front‑to‑back trading and risk‑management processes, preferably in commodities or asset‑intensive trading.

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Cargill

Genève