Head of Data Platform
$176,900–$271,170 year
HybridHouston, Texas, United States
Job Summary
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.
Required Qualifications
- 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
- Must be willing and able to comply with all ENGIE ethics and safety policies
- This role is eligible for our hybrid work policy; a minimum of 3 days working in the offer per week
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