Head of Data Platform
- 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 decisions, and sustain momentum in a highly matrixed environment
- This role is eligible for our hybrid work policy; a minimum of 3 days working in the offer per week
- Must be willing and able to comply with all ENGIE ethics and safety policies;
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