Scientific Games is the global leader in lottery games, sports betting and technology, and they are seeking a Head of Data & AI Platform & Infrastructure. The role involves architecting the Sovereign Platform to provide a seamless environment for Data Science and analytics while managing infrastructure and ensuring technical efficiency.
Responsibilities:
- Architect "Maturity-Grade" Data & AI environment specifically enabling:
- Ingestion Services: Partner with key technical stakeholders to define "Contract" between extraction/collection and platform ingestion
- Unified Medallion Lifecycle Management: Low-latency landing zone coupled with transformation pipelines for silver and gold layer data processing
- Semantic Layer Architecture: Design and maintain a semantic layer that standardizes business logic across the enterprise
- Self-Service Analytics Tooling: Deploy automated, self-service environments that empower downstream business users to create reports and analysis without engineering intervention
- MLOps Lifecycle: Automated pipelines for training, shadow deployment, and live production serving
- Inference Engines: Low-latency infrastructure for real-time model scoring in digital and retail environments
- FinOps & Strategic Cost Management: Act as the primary steward of the technology budget
- Cloud Economics: Implement rigorous tagging, monitoring, and automated scaling to manage Databricks/Cloud consumption and drive high ROI
- Technical Efficiency: Relentlessly pursue the goal of infrastructure savings through modernization
- Legacy Retirement & Technical Debt: Lead the "Sunset Program" for legacy analytics platforms
- Identify, migrate, and decommission redundant systems to simplify footprint and redirect maintenance spend toward innovation
- Ensure the Sovereign Platform integrates seamlessly with the diverse array of digital gaming, retail lottery, and supply chain systems
- Governance & Sovereignty: Ensure that every data asset is governed, discoverable, and secure
- Leadership: Recruit and mentor top class talents across ensuring high technical standards and a focus on commercial outcomes