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- 10+ years of experience in data platforms, data engineering, cloud data architecture, or a related domain.
- 5+ years of experience leading managers, senior engineers, architects, and global technical teams.
- Deep expertise in modern data platform architectures, including lakehouse and cloud-native data ecosystems.
- Hands-on experience with enterprise-scale cloud platforms, particularly Azure and/or AWS.
- Strong knowledge of Databricks or comparable large-scale analytics platforms.
- Experience delivering AI and GenAI platform capabilities, including MLOps, LLMOps, RAG, vector search, model serving, and AI-powered analytics.
- Strong background in Infrastructure as Code, automation, DevOps, and platform engineering.
- Proven success driving cloud FinOps, governance, cost optimization, and operational excellence initiatives.
- Familiarity with data governance, master data management, integration platforms, and enterprise data management practices.
- Experience operating within complex, highly regulated environments is highly desirable.
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related discipline; advanced degree preferred.