Head of Data Platform

You are a senior engineering leader responsible for building and operating the enterprise-grade data and AI platform that underpins ENGIE Energy Marketing North America (EEMNA)’s trading, risk, and operational systems.

As the Head of Data Platform, you own the end-to-end data platform stack—including ingestion, storage, processing, access, and AI enablement—and operate it as a core shared service across all functional teams, supporting Trading Systems, Risk, Analytics, Quant, and Engineering/Infrastructure platforms.

You serve as a Functional Team Lead (FTL) with accountability for multiple Tier-0 services, directly impacting revenue, risk management, and operational resilience.

You drive enterprise-wide change and adoption by aligning teams and increasing platform usage across historically siloed organizations. Adoption—not delivery alone—is your defining measure of success.

You operate in an engineering-first, platform-product role—not a reporting, BI, or data ownership function. Business domains retain ownership of their data, and you enable them through a high-performance, secure, and governed platform.

In this role, you will:

• Own the design, delivery, and operation of the EEMNA enterprise data platform, including real-time and batch ingestion, lakehouse architecture, and enterprise data access
• Ensure Tier-0 reliability, scalability, performance, and production-grade operational standards across all platform services
• Build and operate the AI/ML and Generative AI platform, including model lifecycle infrastructure, feature stores, and AI-ready data environments
• Deploy production-grade AI and agentic solutions to enhance trading and risk decision-making, improve model explainability, and automate key workflows
• Lead AI governance and Center of Excellence initiatives, establishing policies, controls, and frameworks for safe and scalable AI adoption
• Own platform security and data entitlements, including access controls, IAM integration, and protection of critical trading and operational data
• Operate the data platform as a product by delivering self-service capabilities, standardizing tooling and APIs, and improving developer experience
• Lead the Datastone transformation program by consolidating fragmented tooling and aligning with ENGIE enterprise architecture standards
• Own end-to-end accountability for Tier-0 services, including SLOs/SLAs, resilience, and operational discipline
• Partner across Trading, Risk, Analytics, Quant, and Engineering teams to enable standardized platform usage and reduce siloed solutions
• Drive enterprise-wide platform adoption by aligning stakeholders, retiring duplicative systems, and establishing a clear technical direction
• Lead and develop a high-performing data platform organization, including managing senior leaders and building top-tier engineering talent

• Bachelor’s degree in Computer Science, Engineering, Information Technology, Management Information Systems, or a related field
• Minimum of 15 years of experience in data platform engineering, distributed systems, or infrastructure
• Proven experience building and operating large-scale, cloud-native, mission-critical data platforms
• Strong expertise in data pipelines (real-time and batch), lakehouse and data warehouse architectures, and multi-cloud environments (AWS, Azure)
• Demonstrated experience operating production-critical systems with strict reliability, availability, and performance requirements
• Proven track record of delivering measurable platform outcomes, including improvements in data availability, system reliability, and time-to-deliver data capabilities
• Experience building and scaling AI/ML-enabled platforms or enabling AI-driven workflows in production environments
• Demonstrated leadership experience managing high-performing engineering teams, including senior leaders, in complex environments
• Ability to operate at both strategic and hands-on levels, balancing long-term platform vision with near-term execution
• Proven ability to drive cross-functional alignment and adoption across trading, risk, operations, and engineering teams
• Strong ownership and accountability, with the ability to define direction, make…